I help devs build on EVM w/o getting stuck. Dev Rel 🥑 @injective ▹ @DevRelUni + @developer_dao + @hedera + @Rootstock + @DAppsDev ▹ https://xitter.cf/t.co/IyhHZRWPjt
Singapore
Joined June 2009
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Before: 3+ hours on a plan. Exhausting.
After: 5 bullets. ~15 minutes. PRD ready to build!
In June, I gave a talk at Agentic Builders Collective about using the grill-with-docs agent skill by @mattpocockuk and the shaping agent skill by @rjs in a highly customised way.
You know who your developers are, but what path do they take through your platform? Use this agent skill to speedrun what used to take several days to work out and present!
It does the grunt-work parts of the process; all you need to do is answer questions about the persona.
ALT interactive/editable developer journey map produced using the devrel-journey-map agent skill
ALT SKILL.md file of devrel-journey-map agent skill on Github
You'll get an editable journey map at the end of it, in the style of the format used in the @DevRelBook by @jamesparton & @CarolineLewko.
npx skills add -g bguiz/devrel-agent-skills --skill devrel-journey-map
10 best practices for agent skill evals from @_philschmid's talk at AI Engineer:
(1) better descriptions for accurate triggers
(2) more directives, less passive info
(3) evals for negative cases
(4) start set with real prompts, then expand out
(5) unexpected execution paths to good outcomes are OK
(6) isolate runs
(7) pass^k > pass@k
(8) run in multiple harnesses
(9) start with low pass rates, and gradually ramp up
(10) detect when a skill is no longer needed
More notes:
- Prompt sets -> Inputs and correct/expected outputs for each
- CLI runner -> agents exec runner
- Fast regex checks -> skip LLM calls to check output correctness in many cases, less expensive/ faster
- LLM as judge -> LLM calls to check output correctness, more expensive/slower
- Keep evals machine readable (JSON/YAML)
At the @aiDotEngineer World's Fair, I gave a talk on why vibe-checking agent skills breaks in production and how to build reliable automated evals before your users find the bugs. I talked about:
🎯 Why vague descriptions cause skill failures and how adding negative test cases prevents keyword hijacking on unrelated prompts
✂️ Why skill files over 500 lines degrade model reasoning
⚡ How to validate outcomes using simple, millisecond regex assertions across 10 to 20 production prompts.
🗑️ How to run ablation tests (with vs. without skills) to know when models have caught up and you can retire skills.
Check out the full talk and resources below:
Brendan Graetz 🥷 retweeted
Build, deploy, and verify a smart contract on Injective in one prompt.
The Injective MCP server gives your coding agent the tools to do it. Tell it what the contract should do, ask it to deploy and verify, and it hands back a live contract address.
Let the agent do the work. 🥷
Brendan Graetz 🥷 retweeted
with @injective’s x402 protocol, ai agents (or any client) can pay per-request in usdc via http’s unused 402 code.
created a tutorial on how to gate an endpoint with the x402 package and also pay one as a client.
github.com/Ninja-Labs-Devs/i…
cc: @bguiz @ericinjective
had a blast talking about the hard parts of building with gen AI at agentic builders collective SG last night!
great talks all round from @AntonEliasson @ChristianPecaut @jensenloke @yjsoon and yi sheng
... so many great questions from the audience too, love the energy!
icymi: m.youtube.com/watch?v=VPjUgp…
you may have heard me rant about how gen AI is accelerating dead internet theory. this gives me hope that all's not lost on that front:
been on a nostalgia binge with 90s DOS games I used to play
it's been so long I was having trouble even remembering their names
figured out most of them with the help of lots of googling and AI prompts.
... but 1 of them evaded me for almost a week now!
(I could describe the starting scene, but not much else about the game itself)
yesterday I learnt that there was a subreddit just for crowdsourced recall of games that you've forgotten: /r/tipofmyjoystick
& it delivered overnight! TIL the name of the game:
reddit.com/r/tipofmyjoystick…
![[DOS][1990-1995]
SOLVED: Mixed-Up Fairy Tales, 1991, Sierra.
Checklist:
- [x] bookshelf
- [x] gramophone
- [x] dragon
- [ ] dragon is smoking a pipe
- [x] dragon is NPC in start scene
- [x] exit door to enter into forest with forest paths
- [x] point-and-click 1-screen-at-a-time adventure game
- [x] educational puzzles related to English/reading/books
Original post below:
----
What I mainly recall is the start of the game, or at least one specific "scene" from the game, where you start inside the living room of a house:
- there's a dragon smoking a pipe who lives there a pipe sitting in an arm chair
- dragon gives you the "start of game instructions".
- there's a gramophone and a lot of books in a bookshelf.
- when you exit the the main door, you realise the house was hollowed out of a tree trunk
- this tree is on the left side of the screen, and you're in a forest
- there's a path for you to walk along, it's a point and click style adventure game
- there's some educational puzzles](https://pbs.twimg.com/media/HLpNhVVbYAA72W9.jpg?name=orig)
ALT [DOS][1990-1995] SOLVED: Mixed-Up Fairy Tales, 1991, Sierra. Checklist: - [x] bookshelf - [x] gramophone - [x] dragon - [ ] dragon is smoking a pipe - [x] dragon is NPC in start scene - [x] exit door to enter into forest with forest paths - [x] point-and-click 1-screen-at-a-time adventure game - [x] educational puzzles related to English/reading/books Original post below: ---- What I mainly recall is the start of the game, or at least one specific "scene" from the game, where you start inside the living room of a house: - there's a dragon smoking a pipe who lives there a pipe sitting in an arm chair - dragon gives you the "start of game instructions". - there's a gramophone and a lot of books in a bookshelf. - when you exit the the main door, you realise the house was hollowed out of a tree trunk - this tree is on the left side of the screen, and you're in a forest - there's a path for you to walk along, it's a point and click style adventure game - there's some educational puzzles
codex pro tip: if you want < annoying than "ask"/"auto" mode, and > secure than YOLO, there's a p solid in-between: sandbox
codex exec --sandbox workspace-write "... your prompt"
(use this to see the diff with and without)
![// .codex/config.toml
[sandbox_workspace_write]
writable_roots = [
"/Users/bguiz/code/foo/",
"/Users/bguiz/code/bar/"
]](https://pbs.twimg.com/media/HLfUJGdbMAA2Kqs.png?name=orig)
ALT // .codex/config.toml [sandbox_workspace_write] writable_roots = [ "/Users/bguiz/code/foo/", "/Users/bguiz/code/bar/" ]
the hard parts of building with gen AI - lightning talk at @OpenAI SG meetup last night
wanna catch the full version? come to agentic builders SG on mon 29th: luma.com/lfqu9yrk
thx @gabrielchua @brianchew @OpenAI @GrabSG
@bguiz 's talk was the bit that feels more useful the longer you sit with it.
if coding used to be 90% of the pain, codex makes that part cheap enough that the bottleneck moves somewhere else: planning before code, and review after it.
his workflow was basically: do not throw a vague idea at an agent and hope. turn the idea into a product description, then into implementation specs. use the docs-grilling / PRD / Ryan Singer shaping / breadboarding / ADR chain to make the work concrete. let each step leave behind files so the next fresh context window has an actual handoff, not a vibes summary.
i liked the adversarial bit too: get fresh models or skills to argue with the last output, then have a human skim the files before moving on. no fully automated "own self check own self" loop.
and the practical ending: 100% unit coverage can still produce an app that just does not work, so every epic gets representative happy-path and failure-path manual tests.
very much: the code is cheap now; the spec and trust layer are not.
Brendan Graetz 🥷 retweeted
shoutout to @bguiz, he is not entirely a traditional content creator but an invaluable injective team member whose devrel guidance has been crucial. his thorough tutorial reviews and technical direction didn't just help me better understand how to build on the chain, but his mentorship genuinely opened the door and gave me the opportunity to contribute to the ecosystem.
my biggest takeaway from working through his materials and feedback is that a network's infrastructure is only as strong as the team supporting the builders. having that direct, expert guidance is what transforms complex technical frameworks into actual, scalable deployment.
referencing his devrel guidance and writing here: blog.bguiz.com
team name: Hollow Ninjas
WEEK 3 | TASK 3
100 $INJ SQUAD CHALLENGE
for this quest, find an injective creator whose content helped you learn something new or better understand the ecosystem.
tell us what you learned and add your own insight or takeaway.
how to join:
→ quote this post + make sure to tag your creator
→ include links to the content you're referencing
→ include your team name
let's give some well deserved recognition to the creators helping the community learn and grow.
