alt Hacker NewsThe Agentic AI Handbook: Production-Ready Patterns
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I’d rather just read the prompt that this article was generated from.
Not wanting to be a gatekeeper, but the author appears to be a "AI Growth Innovator" or some-such-I-don't-know-what rather than an actual engineer who has been ramping up on AI use to see what works in production:
Scaled GitHub stars to 20,000+
Built engaged communities across platforms (2.8K X, 5.4K LinkedIn, 700+ YouTube)
etc, etc.
No doubt impressive to marketing types but maybe a pinch of salt required for using AI Agents in production.
Not only is the website layout horrible to read, it also smells like the article was written by AI. My brain just screams "no" when I try to read that.
AI written article about AI usage, building things with AI that others will use to build their own AI with. The future is now indeed.
So it begins, Design Patterns and Agile/Scrum snake oil of modern times.
The emergence of this kind of thing has been so surprising to me. The exact same sort of person that managed to bottleneck themselves and obliterate signal-to-noise ratios at every company they work for with endless obsession over the trivial minutiae of the systems they are working with have found a way to do it with LLMs, too, which I would have assumed would have been the death of this kind of busywork
It's unbelievable how productive AI has made me. With the release of the latest Claude, I'm now able to achieve 100x more than I could have without it.
In one week, I fine-tuned https://github.com/kstenerud/bonjson/ for maximum decoding efficiency and:
* Had Claude do a go version (https://github.com/kstenerud/go-bonjson), which outperforms the JSON codec.
* Had Claude do a Rust version (https://github.com/kstenerud/rs-bonjson), which outperforms the JSON codec.
* Had Claude do a Swift version (https://github.com/kstenerud/swift-bonjson), which outperforms the JSON codec (although this one took some time due to the Codable, Encoder, Decoder interfaces).
* Have Claude doing a Python version with Rust underpinnings (making this fast is proving challenging)
* Have Claude doing a Jackson version (in progress, seems to be not too bad)
In ONE week.
This would have taken me a year otherwise, getting the base library going, getting a test runner going for the universal tests, figuring out how good the SIMD support is and what intrinsics I can use, what's the best tooling for hot path analysis, trying various approaches, etc etc. x5.
Now all I do is give Claude a prompt, a spec, and some hand-holding for the optimization phase (admittedly, it starts off at 10x slower, so you have to watch the algorithms it uses). But it's head-and-shoulders above what I could do in the last iteration of Claude.
I can experiment super quickly: Try caching previously encountered keys and show me the performance change. 5 mins, done. Would take me a LOT longer to retool the code just for a quick test. Experiments are dirt cheap now.
The biggest bottleneck right now is that I keep hitting my token limits 1-2 hours before each reset ;-)
Here's a pattern I noticed - you notice some pattern that is working (let's say planning or TODO management) - if the pattern is indeed solid then it gets integrated into the black box and your agent starts doing that internally. At which point your abstraction on top becomes defective because agents get confused about planning the planning.
So with the top performers I think what's most effective is just stating clearly what the end result you want to be (with maybe some hints for verification of results which is just clarifying the intent more)
I sometimes feel like the cognitive cost of agentic coding is so much higher than a skilled human. There is so much more bootstrap and handling process around making sure agents don't go off the rails (they will), or that they will adhere to their goals (they won't). And in my experience fixing issues downstream takes more effort than solving the issue at the root.
The pipe dream of agents handling Github Issue -> PullRequest -> Resolve Issue becomes a nightmare of fixing downstream regressions or other chaos unleashed by agents given too much privilege. I think people optimistic on agents are either naive or hype merchants grifting/shilling.
I can understand the grinning panic of the hype merchants because we've collectively shovelled so much capital into AI with very little to show for it so far. Not to say that AI is useless, far from it, but there's far more over-optimism than realistic assessment of the actual accuracy and capabilities.
If you are interested here is a list of actual agentic patterns - https://go.cbk.ai/patterns
> The Real Bottleneck: Time
Already a "no", the bottleneck is "drowning under your own slop". Ever noticed how fast agents seems to be able to do their work in the beginning of the project, but the larger it grows, it seems to get slower at doing good changes that doesn't break other things?
This is because you're missing the "engineering" part of software engineering, where someone has to think about the domain, design, tradeoffs and how something will be used, which requires good judgement and good wisdom regarding what is a suitable and good design considering what you want to do.
Lately (last year or so), more client jobs of mine have basically been "Hey, so we have this project that someone made with LLMs, they basically don't know how it works, but now we have a ton of users, could you redo it properly?", and in all cases, the applications have been built with zero engineering and with zero (human) regards to design and architecture.
I have no yet have any clients come to me and say "Hey, our current vibe-coders are all busy and don't have time, help us with X", it's always "We've built hairball X, rescue us please?", and that to me makes it pretty obvious what the biggest bottleneck with this sort of coding is.
Moving slower is usually faster long-term granted you think about the design, but obviously slower short-term, which makes it kind of counter-intuitive.
This is a great consolidation of various techniques and patterns for agentic coding. It’s valuable just to standardize our vocabulary in this new world of AI led or assisted programming. I’ve seen a lot of developers all converging toward similar patterns. Having clear terms and definitions for various strategies can help a lot in articulating the best way to solve a given problem. Not so different from approaching a problem and saying “hey, I think we’d benefit from TDD here.”
You should definitely read the whole thing, but tl;dr
- Generate a stable sequence of steps (a plan), then carry it out. Prevents malicious or unintended tool actions from altering the strategy mid-execution and improves reliability on complex tasks.
- Provide a clear goal and toolset. Let the agent determine the orchestration. Increases flexibility and scalability of autonomous workflows.
- Have the agent generate, self-critique, and refine results until a quality threshold is met.
- Provide mechanisms to interrupt and redirect the agent’s process before wasted effort or errors escalate. Effective systems blend agent autonomy with human oversight. Agents should signal confidence and make reasoning visible; humans should intervene or hand off control fluidly.
Why is this at the top?
I've flagged it, that's what we should be doing with AI content.
If you're remotely interested in this type of stuff then scan papers arxiv[0] and you'll start to see patterns emerge. This article is awful from a readability standpoint and from an "does this author give me the impression they know what they're talking about" impression.
But scrap that, it's better just thinking about agent patterns from scratch. It's a green field and, unless you consider yourself profoundly uncreative, the process of thinking through agent coordination is going to yield much greater benefit than eating ideas about patterns through a tube.
0: https://arxiv.org/search/?query=agent+architecture&searchtyp...
The word cost is mentioned only twice in the entire article, lol
Am I the only one with scrolling issues in Firefox on this website?
It literally gets "stuck" and becomes un-scrollable.
looks to be a good resource with lots of links
thanks for the share!
All of this might as well be greek to me. I use ChatGPT and copy paste code snippets. Which was bleeding edge a year or two ago, and now it feels like banging rocks together when reading these types of articles. I never had any luck integrating agents, MCP, using tools etc.
Like if I'm not ready to jump on some AI-spiced up special IDE, am I then going to just be left banging rocks together? It feels like some of these AI agent companies just decided "Ok we can't adopt this into the old IDE's so we'll build a new special IDE"?_Or did I just use the wrong tools (I use Rider and VS, and I have only tried Copilot so far, but feel the "agent mode" of Copilot in those IDE's is basically useless).