Real-Real-World Programming with ChatGPT – O’Reilly

Should you’re studying this, chances are high you’ve performed round with utilizing AI instruments like ChatGPT or GitHub Copilot to put in writing code for you. And even when you haven’t but, then you definately’ve at the least heard about these instruments in your newsfeed over the previous 12 months. To date I’ve learn a gazillion weblog posts about folks’s experiences with these AI coding help instruments. These posts usually recount somebody attempting ChatGPT or Copilot for the primary time with a number of easy prompts, seeing the way it does for some small self-contained coding duties, after which making sweeping claims like “WOW this exceeded all my highest hopes and wildest goals, it’s going to interchange all programmers in 5 years!” or “ha look how incompetent it’s … it couldn’t even get my easy query proper!”

I actually wished to transcend these fast intestine reactions that I’ve seen a lot of on-line, so I attempted utilizing ChatGPT for a number of weeks to assist me implement a interest software program challenge and took notes on what I discovered attention-grabbing. This text summarizes what I realized from that have. The inspiration (and title) for it comes from Mike Loukides’ Radar article on Real World Programming with ChatGPT, which shares an identical spirit of digging into the potential and limits of AI instruments for extra sensible end-to-end programming duties.

Be taught sooner. Dig deeper. See farther.

Setting the Stage: Who Am I and What Am I Attempting to Construct?

I’m a professor who’s concerned with how we are able to use LLMs (Giant Language Fashions) to show programming. My scholar and I just lately revealed a research paper on this subject, which we summarized in our Radar article Teaching Programming in the Age of ChatGPT. Our paper reinforces the rising consensus that LLM-based AI instruments equivalent to ChatGPT and GitHub Copilot can now resolve lots of the small self-contained programming issues which might be present in introductory courses. For example, issues like “write a Python perform that takes an inventory of names, splits them by first and final title, and kinds by final title.” It’s well-known that present AI instruments can resolve these sorts of issues even higher than many college students can. However there’s an enormous distinction between AI writing self-contained features like these and constructing an actual piece of software program end-to-end. I used to be curious to see how properly AI may assist college students do the latter, so I wished to first attempt doing it myself.

I wanted a concrete challenge to implement with the assistance of AI, so I made a decision to go along with an concept that had been behind my head for some time now: Since I learn a whole lot of analysis papers for my job, I usually have a number of browser tabs open with the PDFs of papers I’m planning to learn. I assumed it might be cool to play music from the 12 months that every paper was written whereas I used to be studying it, which supplies era-appropriate background music to accompany every paper. For example, if I’m studying a paper from 2019, a well-liked tune from that 12 months may begin enjoying. And if I change tabs to view a paper from 2008, then a tune from 2008 may begin up. To supply some coherence to the music, I made a decision to make use of Taylor Swift songs since her discography covers the time span of most papers that I sometimes learn: Her main albums were released in 2006, 2008, 2010, 2012, 2014, 2017, 2019, 2020, and 2022. This selection additionally impressed me to name my challenge Swift Papers.

Swift Papers felt like a well-scoped challenge to check how properly AI handles a sensible but manageable real-world programming job. Right here’s how I labored on it: I subscribed to ChatGPT Plus and used the GPT-4 mannequin in ChatGPT (first the Could 12, 2023 model, then the Could 24 model) to assist me with design and implementation. I additionally put in the newest VS Code (Visible Studio Code) with GitHub Copilot and the experimental Copilot Chat plugins, however I ended up not utilizing them a lot. I discovered it simpler to maintain a single conversational circulate inside ChatGPT moderately than switching between a number of instruments. Lastly, I attempted to not seek for assistance on Google, Stack Overflow, or different web sites, which is what I might usually be doing whereas programming. In sum, that is me attempting to simulate the expertise of relying as a lot as attainable on ChatGPT to get this challenge achieved.

Getting Began: Setup Trials and Tribulations

Right here’s the precise immediate I used to begin my dialog with ChatGPT utilizing GPT-4:

Act as a software program developer to assist me construct one thing that may play music from a time interval that matches when a tutorial paper I’m studying within the browser was written.

I purposely stored this immediate high-level and underspecified since I wished ChatGPT to information me towards design and implementation concepts with out me coming in with preconceived notions.

ChatGPT instantly instructed a promising course—making a browser extension that will get the date of the analysis paper PDF within the currently-active tab and calls a music streaming API to play a tune from that point interval. Since I already had a YouTube Music account, I requested whether or not I may use it, however ChatGPT mentioned that YouTube Music doesn’t have an API. We then brainstormed various concepts like utilizing a browser automation software to programmatically navigate and click on on components of the YouTube Music webpage. ChatGPT gave me some concepts alongside these traces however warned me that, “It’s vital to notice that whereas this method doesn’t use any official APIs, it’s extra brittle and extra topic to interrupt if YouTube Music modifications their web site construction. […] remember the fact that net scraping and browser automation will be advanced, and dealing with all the edge instances could be a vital quantity of labor. […] utilizing APIs is likely to be a extra dependable and manageable resolution.” That warning satisfied me to drop this concept. I recalled that ChatGPT had really useful the Spotify Web API in an earlier response, so I requested it to show me extra about what it may possibly do and inform me why I ought to use it moderately than YouTube Music. It appeared like Spotify had what I wanted, so I made a decision to go along with it. I appreciated how ChatGPT helped me work by the tradeoffs of those preliminary design choices earlier than diving head-first into coding.

Subsequent we labored collectively to arrange the boilerplate code for a Chrome browser extension, which I’ve by no means made earlier than. ChatGPT began by producing a manifest.json file for me, which holds the configuration settings that each Chrome extension wants. I didn’t realize it on the time, however manifest.json would trigger me a bunch of frustration afterward. Particularly:

• ChatGPT generated a manifest.json file within the previous Model 2 (v2) format, which is unsupported within the present model of Chrome. For a number of years now Google has been transitioning developers to v3, which I didn’t learn about since I had no prior expertise with Chrome extensions. And ChatGPT didn’t warn me about this. I guessed that possibly ChatGPT solely knew about v2 because it was educated on open-source code from earlier than September 2021 (its information cutoff date) and v2 was the dominant format earlier than that date. Once I tried loading the v2 manifest.json file into Chrome and noticed the error message, I advised ChatGPT “Google says that manifest model 2 is deprecated and to improve to model 3.” To my shock, it knew about v3 from its coaching information and generated a v3 manifest file for me in response. It even advised me that v3 is the currently-supported model (not v2!) … but it nonetheless defaulted to v2 with out giving me any warning! This pissed off me much more than if ChatGPT had not identified about v3 within the first place (in that case I wouldn’t blame it for not telling me one thing that it clearly didn’t know). This theme of sub-optimal defaults will come up repeatedly—that’s, ChatGPT ‘is aware of’ what the optimum selection is however gained’t generate it for me with out me asking for it. The dilemma is that somebody like me who’s new to this space wouldn’t even know what to ask for within the first place.
• After I obtained the v3 manifest working in Chrome, as I attempted utilizing ChatGPT to assist me add extra particulars to my manifest.json file, it tended to “drift” again to producing code in v2 format. I needed to inform it a number of occasions to solely generate v3 code to any extent further, and I nonetheless didn’t totally belief it to observe my directive. In addition to producing code for v2 manifest information, it additionally generated starter JavaScript code for my Chrome extension that works solely with v2 as an alternative of v3, which led to extra mysterious errors. If I have been to begin over realizing what I do now, my preliminary immediate would have sternly advised ChatGPT that I wished to make an extension utilizing v3, which might hopefully keep away from it main me down this v2 rabbit gap.
• The manifest file that ChatGPT generated for me declared the minimal set of permissions—it solely listed the activeTab permission, which grants the extension restricted entry to the lively browser tab. Whereas this has the advantage of respecting person privateness by minimizing permissions (which is a greatest apply that ChatGPT might have realized from its coaching information), it made my coding efforts much more painful since I stored working into surprising errors once I tried including new performance to my Chrome extension. These errors usually confirmed up as one thing not working as meant, however Chrome wouldn’t essentially show a permission denied message. Ultimately, I had so as to add 4 further permissions—”tabs”,  “storage”, “scripting”, “identification”—in addition to a separate “host_permissions” discipline to my manifest.json.

Wrestling with all these finicky particulars of manifest.json earlier than I may start any actual coding felt like dying by a thousand cuts. As well as, ChatGPT generated different starter code within the chat, which I copied into new information in my VS Code challenge:

Intermission 1: ChatGPT as a Customized Tutor

As proven above, a typical Chrome extension like mine has at the least three JavaScript information: a background script, a content material script, and a pop-up script. At this level I wished to study extra about what all these information are supposed to do moderately than persevering with to obediently copy-paste code from ChatGPT into my challenge. Particularly, I found that every file has totally different permissions for what browser or web page parts it may possibly entry, so all three should coordinate to make the extension work as meant. Usually I might learn tutorials about how this all matches collectively, however the issue with tutorials is that they aren’t custom-made to my particular use case. Tutorials present generic conceptual explanations and use made-up toy examples that I can’t relate to. So I find yourself needing to determine how their explanations might or might not apply to my very own context.

In distinction, ChatGPT can generate personalised tutorials that use my very own Swift Papers challenge as the instance in its explanations! For example, when it defined to me what a content material script does, it added that “On your particular challenge, a content material script can be used to extract info (the publication date) from the tutorial paper’s webpage. The content material script can entry the DOM of the webpage, discover the component that comprises the publication date, and retrieve the date.” Equally, it taught me that “Background scripts are perfect for dealing with long-term or ongoing duties, managing state, sustaining databases, and speaking with distant servers. In your challenge, the background script may very well be answerable for speaking with the music API, controlling the music playback, and storing any information or settings that have to persist between searching classes.”

I stored asking ChatGPT follow-up inquiries to get it to show me extra nuances about how Chrome extensions labored, and it grounded its explanations in how these ideas utilized to my Swift Papers challenge. To accompany its explanations, it additionally generated related instance code that I may check out by working my extension. These explanations clicked properly in my head as a result of I used to be already deep into engaged on Swift Papers. It was a significantly better studying expertise than, say, studying generic getting-started tutorials that stroll by creating instance extensions like “track your page reading time” or “remove clutter from a webpage” or “manage your tabs better” … I couldn’t deliver myself to care about these examples since THEY WEREN’T RELEVANT TO ME! On the time, I cared solely about how these ideas utilized to my very own challenge, so ChatGPT shined right here by producing personalised mini-tutorials on-demand.

One other nice side-effect of ChatGPT instructing me these ideas instantly inside our ongoing chat dialog is that at any time when I went again to work on Swift Papers after a number of days away from it, I may scroll again up within the chat historical past to assessment what I just lately realized. This strengthened the information in my head and obtained me again into the context of resuming the place I final left off. To me, it is a large good thing about a conversational interface like ChatGPT versus an IDE autocomplete interface like GitHub Copilot, which doesn’t go away a hint of its interplay historical past. Despite the fact that I had Copilot put in in VS Code as I used to be engaged on Swift Papers, I hardly ever used it (past easy autocompletions) since I appreciated having a chat historical past in ChatGPT to refer again to in later classes.

Subsequent Up: Selecting and Putting in a Date Parsing Library

Ideally Swift Papers would infer the date when a tutorial paper was written by analyzing its PDF file, however that appeared too exhausting to do since there isn’t a typical place inside a PDF the place the publication date is listed. As an alternative what I made a decision to do was to parse the “touchdown pages” for every paper that comprises metadata equivalent to its title, summary, and publication date. Many papers I learn are linked from a small handful of internet sites, such because the ACM Digital Library, arXiv, or Google Scholar, so I may parse the HTML of these touchdown pages to extract publication dates. For example, right here’s the touchdown web page for the traditional Beyond being there paper:

I wished to parse the “Revealed: 01 June 1992” string on that web page to get 1992 because the publication 12 months. I may’ve written this code by hand, however I wished to attempt utilizing a JavaScript date parsing library since it might be extra strong up to now format variations that seem on varied web sites (e.g., utilizing “22” for the 12 months 2022). Additionally, since any real-world software program challenge might want to use exterior libraries, I wished to see how properly ChatGPT may assist me select and set up libraries.

ChatGPT instructed two libraries for me: Moment.js and chrono-node. Nonetheless, it warned me about Second.js: “as of September 2020, it’s thought of a legacy challenge and never really useful for brand new initiatives because the workforce isn’t planning on doing any new growth or upkeep.” I verified this was true by seeing the identical warning on the Second.js homepage. However nonetheless, I appreciated how Second.js was accessible as a single self-contained file that I may instantly embody into my extension with out utilizing a package deal supervisor like npm or a bundler like webpack (the less exterior instruments I wanted to arrange, the higher!). Or so I assumed … ChatGPT led me to imagine that I may get by with out npm and webpack, however later I found that this solely works within the previous Manifest v2 extension format that’s not supported by Chrome. It seems that with Manifest v3, all exterior libraries have to be bundled collectively utilizing instruments like npm and webpack to ensure that the extension to import them. So it goes… as soon as extra I obtained bitten by the truth that ChatGPT was biased towards producing outdated info for v2 moderately than the newer v3, presumably as a result of there was much more details about v2 in its coaching information.

Since I had to make use of npm and webpack anyhow, I made a decision to go along with chrono-node because it appeared extra strong and up-to-date (no pun meant). I had ChatGPT assist me arrange my webpack configuration file (webpack.config.js) and issues virtually appeared to work, besides that I obtained a mysterious error. Once I pasted the error message into ChatGPT, it accurately recognized the issue, which was one thing associated to (shock shock!) webpack’s default settings not being suitable with the safety restrictions of my extension’s Manifest v3 format. It additionally instructed a working repair to webpack.config.js:

This error message is said to the Content material Safety Coverage (CSP) of Chrome extensions. […] By default, Manifest V3 disallows using eval() and the Perform() constructor, that are sometimes used for evaluating or creating code from strings […] Webpack, by default, features a small quantity of inline JavaScript code for dealing with sizzling module alternative and another options. This code makes use of eval() which isn’t allowed within the context of a Chrome extension. To unravel this, you may modify your webpack configuration to output code in a format that doesn’t depend on eval(). In your webpack.config.js, you may set the devtool choice to ‘none’ or use the ‘source-map’ setting […]

Right here once more ChatGPT confirmed me that it clearly knew what the issue was (because it advised me after I fed it the error message!) and the way to repair it. So why didn’t it produce the right webpack configuration file within the first place?

Extra typically, a number of occasions I’ve seen ChatGPT produce code that I felt is likely to be incorrect. Then once I inform it that there is likely to be a bug in a sure half, it admits its mistake and produces the right code in response. If it knew that its unique code was incorrect, then why didn’t it generate the right code within the first place?!? Why did I’ve to ask it to make clear earlier than it admitted its mistake? I’m not an professional at how LLMs work internally, however my layperson guess is that it might should do with the truth that ChatGPT generates code linearly one token at a time, so it might get ‘caught’ close to an area maxima (with code that largely works however is wrong ultimately) whereas it’s navigating the large summary area of attainable output code tokens; and it may possibly’t simply backtrack to appropriate itself because it generates code in a one-way linear stream. However after it finishes producing code, when the person asks it to assessment that code for attainable errors, it may possibly now “see” and analyze all of that code without delay. This complete view of the code might allow ChatGPT to seek out bugs higher, even when it couldn’t keep away from introducing these bugs within the first place on account of the way it incrementally generates code in a one-way stream. (This isn’t an correct technical clarification, however it’s how I informally give it some thought.)

Intermission 2: ChatGPT as a UX Design Marketing consultant

Now that I had a primary Chrome extension that might extract paper publication dates from webpages, the subsequent problem was utilizing the Spotify API to play era-appropriate Taylor Swift songs to accompany these papers. However earlier than embarking on one other coding-intensive journey, I wished to modify gears and assume extra about UX (person expertise). I obtained so caught up within the first few hours of getting my extension arrange that I hadn’t thought of how this app should work intimately. What I wanted at the moment was a UX design marketing consultant, so I wished to see if ChatGPT may play this function.

Observe that up till now I had been doing every little thing in a single long-running chat session that centered on coding-related questions. That was nice as a result of ChatGPT was totally “within the zone” and had a really lengthy dialog (spanning a number of hours over a number of days) to make use of as context for producing code strategies and technical explanations. However I didn’t need all that prior context to affect our UX dialogue, so I made a decision to start once more by beginning a brand-new session with the next immediate:

You’re a Ph.D. graduate in Human-Pc Interplay and now a senior UX (person expertise) designer at a prime design agency. Thus, you might be very acquainted with each the expertise of studying educational papers in academia and in addition designing wonderful person experiences in digital merchandise equivalent to net functions. I’m a professor who’s making a Chrome Extension for enjoyable with a purpose to prototype the next concept: I wish to make the expertise of studying educational papers extra immersive by routinely enjoying Taylor Swift songs from the time interval when every paper was written whereas the reader is studying that specific paper in Chrome. I’ve already arrange all of the code to connect with the Spotify Net API to programmatically play Taylor Swift songs from sure time durations. I’ve additionally already arrange a primary Chrome Extension that is aware of what webpages the person has open in every tab and, if it detects {that a} webpage might comprise metadata about a tutorial paper then it parses that webpage to get the 12 months the paper was written in, with a purpose to inform the extension what tune to play from Spotify. That’s the primary premise of my challenge.

Your job is to function a UX design marketing consultant to assist me design the person expertise for such a Chrome Extension. Don’t worry about whether or not it’s possible to implement the designs. I’m an skilled programmer so I’ll inform you what concepts are or usually are not possible to implement. I simply need your assist with considering by UX design.

As our session progressed, I used to be very impressed with ChatGPT’s potential to assist me brainstorm the way to deal with totally different person interplay situations. That mentioned, I needed to give it some steerage upfront utilizing my information of UX design: I began by asking it to provide you with a number of person personas after which to construct up some person journeys for every. Given this preliminary prompting, ChatGPT was in a position to assist me provide you with sensible concepts that I didn’t initially contemplate all too properly, particularly for dealing with uncommon edge instances (e.g., what ought to occur to the music when the person switches between tabs in a short time?). The back-and-forth conversational nature of our chat made me really feel like I used to be speaking to an actual human UX design marketing consultant.

I had a whole lot of enjoyable working with ChatGPT to refine my preliminary high-level concepts into an in depth plan for the way to deal with particular person interactions inside Swift Papers. The fruits of our consulting session was ChatGPT producing ASCII diagrams of person journeys by Swift Papers, which I may later confer with when implementing this logic in code. Right here’s one instance:

Reflecting again, this session was productive as a result of I used to be acquainted sufficient with UX design ideas to steer the dialog in direction of extra depth. Out of curiosity, I began a brand new chat session with precisely the identical UX marketing consultant immediate as above however then performed the a part of a complete novice as an alternative of guiding it:

I don’t know something about UX design. Are you able to assist me get began since you’re the professional?

The dialog that adopted was far much less helpful since ChatGPT ended up giving me a primary primer on UX Design 101 and providing high-level strategies for a way I can begin fascinated by the person expertise of Swift Papers. I didn’t wish to nudge it too exhausting since I used to be pretending to be a novice, and it wasn’t proactive sufficient to ask me clarifying inquiries to probe deeper. Maybe if I had prompted it to be extra proactive at the beginning, then it may have elicited extra info even from a novice.

This digression reinforces the widely-known consensus that what you get out of LLMs like ChatGPT is simply nearly as good because the prompts you’re in a position to put in. There’s all of this related information hiding inside its neural community mastermind of billions and billions of LLM parameters, however it’s as much as you to coax it into revealing what it is aware of by taking the lead in conversations and crafting the appropriate prompts to direct it towards helpful responses. Doing so requires a level of experience within the area you’re asking about, so it’s one thing that rookies would doubtless wrestle with.

The Final Massive Hurdle: Working with the Spotify API

After ChatGPT helped me with UX design, the final hurdle I needed to overcome was determining the way to join my Chrome extension to the Spotify Web API to pick out and play music. Like my earlier journey with putting in a date parsing library, connecting to net APIs is one other widespread real-world programming job, so I wished to see how properly ChatGPT may assist me with it.

The gold normal right here is an professional human programmer who has a whole lot of expertise with the Spotify API and who is nice at instructing novices. ChatGPT was alright for getting me began however in the end didn’t meet this normal. My expertise right here confirmed me that human specialists nonetheless outperform the present model of ChatGPT alongside the next dimensions:

• Context, context, context: Since ChatGPT can’t “see” my display, it lacks a whole lot of helpful job context {that a} human professional sitting beside me would have. For example, connecting to an online API requires a whole lot of “pointing-and-clicking” guide setup work that isn’t programming: I needed to register for a paid Spotify Premium account to grant me API entry, navigate by its net dashboard interface to create a brand new challenge, generate API keys and insert them into varied locations in my code, then register a URL the place my app lives to ensure that authentication to work. However what URL do I take advantage of? Swift Papers is a Chrome extension working domestically on my pc moderately than on-line, so it doesn’t have an actual URL. I later found that Chrome extensions export a faux chromiumapp.org URL that can be utilized for net API authentication. A human professional who’s pair programming with me would know all these ultra-specific idiosyncrasies and information me by pointing-and-clicking on the assorted dashboards to place all of the API keys and URLs in the appropriate locations. In distinction, since ChatGPT can’t see this context, I’ve to explicitly inform it what I need at every step. And since this setup course of was so new to me, I had a tough time fascinated by the way to phrase my questions. A human professional would have the ability to see me struggling and step in to supply proactive help for getting me unstuck.
• Hen’s-eye view: A human professional would additionally perceive what I’m attempting to do—deciding on and enjoying date-appropriate songs—and information me on the way to navigate the labyrinth of the sprawling Spotify API with a purpose to do it. In distinction, ChatGPT doesn’t appear to have as a lot of a hen’s-eye view, so it eagerly barrels forward to generate code with particular low-level API calls at any time when I ask it one thing. I, too, am wanting to observe its lead because it sounds so assured every time it suggests code together with a convincing clarification (LLMs are inclined to undertake an overconfident tone, even when their responses could also be factually inaccurate). That generally leads me on a wild goose chase down one course solely to comprehend that it’s a dead-end and that I’ve to backtrack. Extra typically, it appears exhausting for novices to study programming on this piecemeal manner by churning by one ChatGPT response after one other moderately than having extra structured steerage from a human professional.
• Tacit (unwritten) information: The Spotify API is supposed to regulate an already-open Spotify participant (e.g., the online participant or a devoted app), to not instantly play songs. Thus, ChatGPT advised me it was not attainable to make use of it to play songs within the present browser tab, which Swift Papers wanted to do. I wished to confirm this for myself, so I went again to “old-school” looking out the online, studying docs, and searching for instance code on-line. I discovered that there was conflicting and unreliable details about whether or not it’s even attainable to do that. And since ChatGPT is educated on textual content from the web, if that textual content doesn’t comprise high-quality details about a subject, then ChatGPT gained’t work properly for it both. In distinction, a human professional can draw upon their huge retailer of expertise from working with the Spotify API with a purpose to train me methods that aren’t well-documented on-line. On this case, I finally discovered a hack to get playback working by forcing a Spotify net participant to open in a brand new browser tab, utilizing a super-obscure and not-well-documented API name to make that participant ‘lively’ (or else it generally gained’t reply to requests to play … that took me perpetually to determine, and ChatGPT stored giving me inconsistent responses that didn’t work), after which enjoying music inside that background tab. I really feel that people are nonetheless higher than LLMs at arising with these kinds of hacks since there aren’t readily-available on-line assets to doc them. A variety of this hard-earned information is tacit and never written down wherever, so LLMs can’t be educated on it.
• Lookahead: Lastly, even in situations when ChatGPT may assist out by producing good-quality code, I usually needed to manually replace different supply code information to make them suitable with the brand new code that ChatGPT was giving me. For example, when it instructed an replace to a JavaScript file to name a selected Chrome extension API perform, I additionally needed to modify my manifest.json to grant an extra permission earlier than that perform name may work (bitten by permissions once more!). If I didn’t know to do this, then I might see some mysterious error message pop up, paste it into ChatGPT, and it might generally give me a technique to repair it. Similar to earlier, ChatGPT “is aware of” the reply right here, however I have to ask it the appropriate query at each step alongside the way in which, which may get exhausting. That is particularly an issue for novices since we regularly don’t know what we don’t know, so we don’t know what to even ask for within the first place! In distinction, a human professional who helps me would have the ability to “look forward” a number of steps based mostly on their expertise and inform me what different information I have to edit forward of time so I don’t get bitten by these bugs within the first place.

Ultimately I obtained this Spotify API setup working by doing a little old style net looking out to complement my ChatGPT dialog. (I did attempt the ChatGPT + Bing net search plugin for a bit, however it was gradual and didn’t produce helpful outcomes, so I couldn’t tolerate it any extra and simply shut it off.) The breakthrough got here as I used to be searching a GitHub repository of Spotify Web API example code. I noticed an instance for Node.js that appeared to do what I wished, so I copy-pasted that code snippet into ChatGPT and advised it to adapt the instance for my Swift Papers app (which isn’t utilizing Node.js):

Right here’s some instance code utilizing Implicit Grant Stream from Spotify’s documentation, which is for a Node.js app. Are you able to adapt it to suit my chrome extension? [I pasted the code snippet here]

ChatGPT did a great job at “translating” that instance into my context, which was precisely what I wanted in the meanwhile to get unstuck. The code it generated wasn’t excellent, however it was sufficient to begin me down a promising path that may ultimately lead me to get the Spotify API working for Swift Papers. Reflecting again, I later realized that I had manually achieved a easy type of RAG (Retrieval Augmented Generation) right here through the use of my instinct to retrieve a small however highly-relevant snippet of instance code from the huge universe of all code on the web after which asking a super-specific query about it. (Nonetheless, I’m undecided a newbie would have the ability to scour the online to seek out such a related piece of instance code like I did, so they might in all probability nonetheless be caught at this step as a result of ChatGPT alone wasn’t in a position to generate working code with out this further push from me.)

Epilogue: What Now?

I’ve a confession: I didn’t find yourself ending Swift Papers. Since this was a interest challenge, I finished engaged on it after about two weeks when my day-job obtained extra busy. Nonetheless, I nonetheless felt like I accomplished the preliminary exhausting components and obtained a way of how ChatGPT may (and couldn’t) assist me alongside the way in which. To recap, this concerned:

• Establishing a primary Chrome extension and familiarizing myself with the ideas, permission settings, configuration information, and code parts that should coordinate collectively to make all of it work.
• Putting in third-party JavaScript libraries (equivalent to a date parsing library) and configuring the npm and webpack toolchain in order that these libraries work with Chrome extensions, particularly given the strict safety insurance policies of Manifest v3.
• Connecting to the Spotify Net API in such a technique to assist the sorts of person interactions that I wanted in Swift Papers and coping with the idiosyncrasies of accessing this API through a Chrome extension.
• Sketching out detailed UX journeys for the sorts of person interactions to assist and the way Swift Papers can deal with varied edge instances.

After laying this groundwork, I used to be in a position to begin stepping into the circulate of an edit-run-debug cycle the place I knew precisely the place so as to add code to implement a brand new function, the way to run it to evaluate whether or not it did what I meant, and the way to debug. So despite the fact that I finished engaged on this challenge on account of lack of time, I obtained far sufficient to see how finishing Swift Papers can be “only a matter of programming.” Observe that I’m not attempting to trivialize the challenges concerned in programming, since I’ve achieved sufficient of it to know that the satan is within the particulars. However these coding-specific particulars are precisely the place AI instruments like ChatGPT and GitHub Copilot shine! So even when I had continued including options all through the approaching weeks, I don’t really feel like I might’ve gotten any insights about AI instruments that differ from what many others have already written about. That’s as a result of as soon as the software program atmosphere has been arrange (e.g., libraries, frameworks, construct techniques, permissions, API authentication keys, and different plumbing to hook issues collectively), then the duty at hand reduces to a self-contained and well-defined programming downside, which AI instruments excel at.

In sum, my objective in writing this text was to share my experiences utilizing ChatGPT for the extra open-ended duties that got here earlier than my challenge became “only a matter of programming.” Now, some might argue that this isn’t “actual” programming because it looks like only a bunch of mundane setup and configuration work. However I imagine that if “real-world” programming means creating one thing sensible with code, then “real-real-world” programming (the title of this text!) encompasses all these tedious and idiosyncratic errands which might be essential earlier than any actual programming can start. And from what I’ve skilled to this point, this kind of work isn’t one thing people can totally outsource to AI instruments but. Lengthy story quick, somebody in the present day can’t simply give AI a high-level description of Swift Papers and have a sturdy piece of software program magically come out the opposite finish. I’m positive folks at the moment are engaged on the subsequent technology of AI that may deliver us nearer to this objective (e.g., much longer context windows with Claude 2 and retrieval augmented generation with Cody), so I’m excited to see what’s in retailer. Maybe future AI software builders may use Swift Papers as a benchmark to evaluate how properly their software performs on an instance real-real-world programming job. Proper now, widely-used benchmarks for AI code technology (e.g., HumanEval, MBPP) include small self-contained duties that seem in introductory courses, coding interviews, or programming competitions. We’d like extra end-to-end, real-world benchmarks to drive enhancements in these AI instruments.

Lastly, switching gears a bit, I additionally wish to assume extra sooner or later about how AI instruments can train novices the abilities they should create sensible software program initiatives like Swift Papers moderately than doing all of the implementation work for them. At current, ChatGPT and Copilot are moderately good “doers” however not practically nearly as good at being lecturers. That is unsurprising since they have been designed to hold out directions like a great assistant would, to not be an efficient instructor who supplies pedagogically-meaningful steerage. With the correct prompting and fine-tuning, I’m positive they will do significantly better right here, and organizations like Khan Academy are already customizing GPT-4 to become a personalized tutor. I’m excited to see how issues progress on this fast-moving area within the coming months and years. Within the meantime, for extra ideas about AI coding instruments in training, take a look at this different current Radar article that I co-authored, Teaching Programming in the Age of ChatGPT, which summarizes our research paper about this subject.