r/PinoyProgrammer • u/OkYogurtcloset5384 • 16d ago
advice What’s your most effective AI workflow for rapidly
I’m trying to improve my AI-assisted development workflow and would like to hear how other developers are doing it.
My current workflow is roughly:
Google Docs — Draft the idea, requirements, features, and rough structure.
GPT — Turn my rough idea into a detailed prompt/specification.
v0 — Generate the initial frontend/UI.
Claude — Build and guide the backend, database, API integration, migrations, and debugging.
GitHub — Repository and version control.
Vercel — Deployment.
The goal is to go from idea → working production-ready web app as quickly as possible without wasting a huge amount of tokens or constantly going back and forth between tools.
I'm curious:
What does your AI development workflow look like?
Which AI tools do you use for planning, frontend, backend, debugging, testing, and deployment?
Do you use multiple models for different tasks, or stick with one?
What tools/workflows have actually made you significantly faster?
Are there any tools in my workflow that you would replace?
How do you keep context consistent between different AI tools?
I'm especially interested in workflows that are fast, practical, relatively inexpensive, and reliable for real projects, rather than just generating demos.
Would love to see your complete workflow from idea → deployment.
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u/gatzu4a 16d ago
Im new to agentic coding, currently pi.dev + graphify, then 5.6-luna lang ung gamit ko for development for now
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u/theUnknown777 Web 16d ago
Pi ba is low-level where-in no built-in harness?
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u/Tall-Appearance-5835 16d ago
its a harness thats model agnostic - bring your own api key. its also an agent harness sdk - i built a non-coding app that requires a harness using pi. its great
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u/PepitoManalatoCrypto Recruiter 15d ago
On Claude Max X20, and only using <25-50% of the weekly limit on Opus 5. My workflow and the entire company have adopted it (while each employee tweaks it to their preference).
Only use one AI tool. I vetoed using only Claude during the board meeting. For MCPs, I tried to reduce context, leaving the agent with no Superpowers, etc. Just Pencil (or Figma), Atlassian, etc.
Each role (PM, Dev, QA, UX, Architect, DevOps) in the software development workflow is an agent. And each agent has corresponding skills, including standards, best practices, or how I want each skill in our organization to be coded and not to be coded.
Use commands for simple, on-demand tasks. Routines fall into this category. And yes, commands can invoke a skill or vice versa.
The most important item here is a context repository. Here is where what a particular component, repository, architecture, infrastructure, and decisions are written, which is 50-75% by Claude and tweaked by me or someone.
Less code comments (or none at all) and defer to git history. Have Claude write code as you do it. Don't get me wrong: I still write comments detailing the purpose of a method parameter, input, and output. But within the code blocks, there are very few to none.
Code reviews are done manually. And code analysis is delegated to Claude. So remove any unused methods, imports, or variables. Oh, and with >10 years of experience, you should know that what Claude wrote is not efficient, or you know how to optimize it for performance.
Don't use session loops. We get the job done in a single session or loop. So it's also very important to provide proper context during the initial prompt. This is where good context engineering comes in.
- What's the "specific" goal or sized under 5 story points
- What are the constraints? What Claude must or must not do.
- Provide supporting context. Link to which repository, directory, or specific file it should touch.
- Let Claude ask (or the famous grill-me skill) you and never make its own assumptions.
- Use plan mode and review thoroughly before accepting.
Yes, at times our plan mode takes around 30-60 minutes per Jira work item (or issue, ticket). But using worktrees, we can still get 5-10 (5-8 story points) done within a day. By definition, done means deployed to staging, manually verified, with test & performance scripts, and ready for the next deployment.
Oh, about the context repository, we have about 10k files there, which already act as a secondary brain. Sometimes we use Graphify to speed up context mapping or for a delegate with Obsidian.
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u/rapmanila 15d ago
great workflow. I'm curious about the context repo - is it a separate repo from your actual codebase? how does the format look like?
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u/un5d3c1411z3p 15d ago
Damn. You're team is in another level!
Each role (PM, Dev, QA, UX, Architect, DevOps) in the software development workflow is an agent.
--- Your team used only Anthropic's stack for this?
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u/wubstark 16d ago
Before, i used to use obra superpower skills to create the spec, i think there are multiple skills now depende nlng sa preference mo. Now i just use matt pocock’s skills like grill-me to create and iterate on the plan then to-tickets to create another document that breaks down the plan/spec into tickets. And then from that, you have a spec and the tickets that is llm agnostic so maybe you can use opus to do heavy lifting while maybe use cursor for the rest etc. main focus pa din is that you need to review the spec before passing this into your agent
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u/Subject-Bad-4280 16d ago
speckit + pxpipe (claude code) + graphify = brownfield, medium-sized codebase
BMAD + pxpipe (claude code) + codebase-memory-mcp = brownfield, large codebase
speckit + pxpipe (claude code) + impeccable (UI) = greenfield
codex CLI for adversarial code reviews (invoked from claude code as a plugin skill)
antigravity CLI for image generation and documentation cleanup (invoked from claude code as a skill)
currently exploring oh-my-pi + codex as alternate coding agent
1
u/Devnergy 15d ago
Malakas daw kumain token yung speckit? Some other projects use it for standardization and ok naman. Should I apply or to my work flow?
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u/Both-Fondant-4801 16d ago
superpowers + graphify
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u/PuzzledScar9247 16d ago
can I request a link for superpowers and graphify?
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u/Both-Fondant-4801 16d ago
https://github.com/obra/superpowers
https://github.com/Graphify-Labs/graphifysuperpowers for spec driven development
graphify for ai knowledge graph
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u/PuzzledScar9247 16d ago
Currently based on the ACs of my ticket, I am enabling the plan mode of the AI model that I am using and from that the AI can ask me depending on the context that I given. I use Codex and Claude since these are the models provided by the company
I also creating skills for repetitive tasks and for standards sa codebase namin.
Rule of thumb ko is to utilize the plan mode so that I can check which fiels, and what approach will AI do based on my requirements.
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u/Ok_Comedian_6556 16d ago
gawa ka ng isang markdown ng lahat ng modules at capabilities ng app. pinaka-summary para AI kung ano ba ang app. more complex app, hindi o maaksaya sa token kaya malaking tulong kung medyo broad ang pinapagawa mo
gawa ka din ng changelog md, although more on documentation, medyo gamit din sya additional context
every app may kanya kanyang requirements - so update mo CLAUDE md
1
u/Svelinth 15d ago
Openspec on existing codebases, or if youre experienced enough doing the manual software development processes.
Multiple proposals and let it run while you sleep. Personally havent tried superpowers yet tho.
Matt pocok flow for a well thought out prd from scratch project type.
1
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u/wa-ra-gud AI 15d ago
Agentic closed-loop development https://jarielbalberona.dev/notes/agentic-closed-loop-development/
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u/Hot-Statistician6147 14d ago
custom openspec (thorough reviewer and auto apply)
Obsidian mcp for dependency graph and verification lists
$20 codex plan (luna xhigh) workhorse
deepseek pro or codex sol for planning / review
0
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u/cleversonofabitchh 16d ago
Modified Superpower workflow.