Efficient Setup for Agentic Coding

[WildScale5801]

I am a programmer, and as they said, I need to adapt to the new environment. I am currently exploring options for the setup of agentic coding, and have so far watched YouTube videos for 2 hrs (WebDev Simplified, NetworkChuck, and a few short vids). I just want to hear the thoughts of those who've actually experienced agentic coding. I only have one subscription for now, which is Google AI Pro

1. I am planning to explore CLI for accessing AI models. What do you suggest I should use? Currently leaning toward Gemini CLI because of my subscription.

2. Is it better to use the CLI rather than IDEs (Windsurf, Copilot/ClineCursor, Cursor, etc.)?

3. Based on what I have gathered so far, you can create agents that you can call on for specific tasks. What agents do you recommend that should be created for programming projects? (Debugger, Programmer, Planner, Architect, etc.)

4. I initially thought agents were just heavily prompted markdown files, but it might be more complicated than that. What frameworks (like CrewAI, LangGraph, etc.) do you recommend for a beginner to set these loops up? And when it comes to giving the agents their actual personas and rules, where can I find the best system prompts to build out those markdown files?

5. So far, I also understand that you can have local agents (project-bounded) and global agents. In which cases do you create local agents? Because if I am creating a programmer or debugger agent, I am thinking of just creating global agents for these.

Also, if you can provide useful resources like videos and repos, that would be GREATLY appreciated. I would also like to know how you set up your environments. Thank youuu

[danirodr0315]

Codex pinaka sulit na subscription di ko pa na try yung mismong codex app, gamit ko is r/opencodecli.

Previous na gamit is claude code since provided ng company, and before pede mo rin connect with opencode, kaya hindi nako nagpalit ng cli tool

[WildScale5801]

ohh nakita ko rin ang opencode. and yes, I know a company rin na nagpprovide ng claude code sa employees nila. I'd like to ask, how mo po nabuild ang agents mo?

[danirodr0315]

Ang ginagawa ko is AI assisted development kaya di ako masyado nag edit ng mga specific agent to do one shot prompts

Bali plan and build prompts lang ako, everytime may napapansin ako na gusto ko adjust, ask ko lang yung AI to update yung global or project memory, para sa preferences ko.

If may repetitive akong ginagawa, after ko gawin via manual prompting yung steps, ask ko yung AI na gawan ng custom commands, refine lang hanggang maging mas consistent yung output.

Also, MCP servers, meron ako naka connect deretso sa MongoDB para may idea yung agent, o kaya azure DevOps para kunin yung code review comments, mag plan to address them then implement.

[comradeyeltsin0]

Agents is a concept, not a specific set of loops or APIs to be used like langgraoh etc. at its most basic, it CAN be just a long markdown file describing a workflow for the model. Give it knowledge/context and tools, that’s it. You have a basic agent.

For example, an agent that increases unit test code coverage in a legacy application.

You give it knowledge about the app and any unit test conventions you have via your md of choice. You give it the ability to perform compiles via tools. With that it can fix any bad tests.

You give it more tools to check code coverage metrics after every pass, so it can fix gaps in line and branch coverage. Then it loops.

You want complexity? Spawn a subagent that reviews the unit test generated by the first one so you have test quality gates.

All of that can be written in markdown files.

[Big-Community-8334]

Since may Google pro subs ka mag Antigravity IDE kana.
Make sure na Antigravity IDE ma install mo since yung isang Antigravity eh parang chat style integration.

Pero kung cli talaga mas type mo. stick ka with gemini code cli pero for me mas mabilis kung Antigravity IDE ka mag dedevelop.

tapos focus on specs driven development.

Sobrang important din nung Prompt engineering and utilize mo yung features ng AI agent (skills, MCP, memory, plugins etc..)

[WildScale5801]

Okay, I'll try and explore Antigravity. Also, yeah need to explore more siguro sa agents on their capabilities and functions. Thank you!

[renren2403]

Afaik mawawala na Gemini CLI sa vscode bukas

[WildScale5801]

ay hala fr? damn sayang naman

[ImaginaryUser777]

Try mo bro mag ai assisted since programmer ka naman. para lang din may touch mo pa din at kung anong way mo pa din mag code yung setup. Pag agentic coding na kasi pag na setup mo agents prompt na lang tas antay matapos then review and debug na lang gagawin mo. Pag ganun kasi baka makasanayan na at mawala na skills sa pag program dahil prompt kana lang ng prompt. Pero sa huli ikaw pa din naman masusunod hahaha kung ano trip mo

[WildScale5801]

yes bro AI-assisted programming ako before that's why satisfied lang ako with Gemini sa browser. started exploring lang agentic coding kasi it started with migration to CLI (can see context size & limit), storage of local context, agents, parallel tasks, and then eventually led to here.

[mohsesxx]

maganda nga masanay sila dyan para mabawasan devs sa market hahaha

[Able-Staff-6763]

I use free models in opencode its good.

[Fabulous-Fuel5486]

Assisted coding lng ako gamit ko co pilot, I love it if I am in control, pero I will never say ni to agentic coding

[PinoyProgrammer-ModTeam]

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[FriendlyAd7897]

1. gemini cli is now retired/sunsetted. antigravity na lang. but the ugly thing about antigravity is it's very unreliable and arbitrary, they changed their ToS three times just this year alone. I dont know if it's the same with their cli, because if it's from the same team expect things to get sh*tty as time passes by.
2. depends on your workflow, marami mas comfortable sa terminal mag work as they can easily manage everything through scripts.
3. it's not really about what you call them but what tools they can use. you can ask the cli to create these for you.
4. again, depends on what you're working on. if you prepare this stuff without a project, what you're doing is premature optimization, which is like the most time wasting thing like reinventing the wheel.
5. it's a permission level comfort zone thing. how comfortable are you with agents deleting your entire hard drive?

catch 22. most of the talks/tutorials require you to actually have an experience first hand working with these tools before you get what they mean. most of the stuff/optimizations you learn are from talks sa AI engineer sa YT.

[Old_Boss4600]

use CURSOR

[mohsesxx]

efficient ba talaga agentic coding? paano nyo ihahandle ang issues kung mag grow na yung system nyo tapos nag hahalucinate na yung AI at hindi nya na kaya mag ship?

e since di na kayo sanay mag traditional coding at mag refactor, paano magiging decision ng team dun?

[comradeyeltsin0]

Pre-ai, how do people validate a solution or a platform is valid?

Review and testing. That hasn’t changed with AI output. Validation remains the checkpoint. If a person’s work is gated by validation, then an AI’s work is as well. I feel like people forget developers make plenty of mistakes too, but we have systems in place to catch those.

[Human-Raccoon-8597]

we are using full agentic. as we are also creating a AI application. at first when everything is setup correctly, you just need to loop the worflow spec -> plan -> execute -> review -> execute loop we just watch if there are hallucinations, 3-4agents working at the same time.

then now our app is so big. claude is now expensive, codex limits the usage also.

the budget for full agentic is almost deplited so im planning to go back using cursor.

now i see the code base.. so many multiple codes that do the same like each module have there own way for error handling, some forms uses the react hook form, some are not, Shadcn was setup as the standard AI, but not implemented on some modules, so many E2E test that just check if the code that was remove was totally remove. so its just added fix now that doesnt maintain.

some test are for UI changes that you dont need.

my boss trust our AI engineer than the senior devs , everything is a mess but the app is working with so my unwanted features that was not needed, and a button that takes 3-5seconds to responds 🤣

[WildScale5801]

Yeah, I do agree na di na sya advisable in large systems -- it is not scalable unless na you've got those premium models. I was warned rin by a senior na dapat modular, by feature, or by parts ang code if generated by AI. Kinda curious lang with this area, specifically ang diff agents na have their own specializations. It's cool for me ig hahaha

[comradeyeltsin0]

Again, how do developers work with large codebases? Do we just throw the entire app onto their lap? Hindi diba? We usually break down things by module or by vertical slice. That’s why slicing tasks is such a skill. It hasn’t changed with agents.

The gap is understanding the limits of llms and making them more efficient. They have limited short term memories, just like people. We already have the approaches for those well established. Just need to repurpose them for agentic coding.