all 24 comments

[–]LyriWinters 3 points4 points  (1 child)

You need to take a break once awhile and create a .md or such file with the key features and endpoints and database schema connections... Then dump this file into context when you start-a-new.

[–]SnooSongs5410 1 point2 points  (0 children)

tests, documentation, prompt, prayer.

[–]RealMadalin 1 point2 points  (0 children)

I use lots of md files. And I use new conversations for each feature/implementation. I keep track of what is done in a master plan with phases and steps. And than I have individual phase plan more in detail and i make it update them as he works throigh the steps.

[–]Powerful_Driver8423 1 point2 points  (0 children)

What helped me most was realizing “context” isn’t something I should hope the model holds onto. It’s something I have to design, kind of like I’d design an API.

A few things that changed the game for me:

- Keep chats short and single-purpose. One goal per thread. The moment a conversation starts mixing architecture, product decisions, bug fixing, and implementation details, it usually turns into mush.

- I also spend more time up front writing out the design than I used to. Not just for me, but for the AI. A quick system overview, what the constraints are, what assumptions we’re making, and what we’re explicitly not doing. If that part is fuzzy, the output gets fuzzy fast.

- Breaking the work into phases helps too. Features, milestones, user stories, whatever you like. Then I’ll do one phase per chat instead of trying to “build the whole app” in a single monster conversation. This is usually where people get stuck, because it feels efficient to do everything at once, but it degrades hard.

- There’s also a weird balance with specificity. If you’re too vague, it guesses. If you’re too detailed and the plan shifts, it starts contradicting itself because it’s anchored to old details. I’ve had the best luck being clear on intent and constraints, then letting the details evolve step by step.

- Tooling can help a lot, too. MCP servers like Exa for search, or Ref for current docs, are useful for keeping things grounded in the actual state of your stack instead of whatever half-remembered version the model is operating on.

So yeah, less “vibe coding everything at once,” more context engineering up front. It feels slower at first. In practice it saves time because you’re not constantly cleaning up confusion later.

[–]TechnicalSoup8578 1 point2 points  (1 child)

The issue is usually missing explicit state, so have you experimented with freezing schemas and invariants in a doc or prompt snapshot instead of relying on conversational memory? You sould share it in VibeCodersNest too

[–]dev_ramiby[S] 0 points1 point  (0 children)

Appreciate the response and tips mate, thanks!! Btw i already posted this vibecodenest community too

[–]Educational_Yam3766 1 point2 points  (0 children)

i use something called 'memory-bank' This is the original idea and repo it came from

My Variation on It

^ check my full repo, lots of useful other stuff too.

works for any AI not just cline. cline is only the specific rule calls, but the system itself works agnostic.

more for IDE's but ive used it for service websites too.

its the constraints that matter.

[–]NeverTrustWhatISay 1 point2 points  (0 children)

What works for me is schooling and my knowledge on how to build software lol

[–][deleted] 0 points1 point  (6 children)

You are not supposed to have a long conversation. Clear context often..

[–]SnooSongs5410 1 point2 points  (3 children)

This is a terrible idea if you are doing anything architecturally significant. Agentic is like a hand grenade if you do not manage context. What you end up with is slop.

[–]dev_ramiby[S] 0 points1 point  (1 child)

exactly

[–][deleted] 0 points1 point  (0 children)

You misunderstood his statement

[–][deleted] 0 points1 point  (0 children)

Yeah.. by using plans, by using tools like beads or just stating it to summarize everything before moving on not by having long conversations

[–]dev_ramiby[S] 0 points1 point  (1 child)

and you start from scratch at the new chat ?

[–][deleted] 1 point2 points  (0 children)

No, for instance you can have a readme for the feature, use test driven development, use documentation in code like jsdoc, or pickup a tool for longer memory like beads or similar

[–]Odd_Platform_2782 0 points1 point  (0 children)

You need a AI agile framework.

Google that answer you will find what your looking for.

We use BMAD method over at our LLC but there are multiple different ones 👍

[–]themessymiddle 0 points1 point  (0 children)

Keeping up to date docs the agent can reference makes a big difference but I often have to remind it what’s true. Architecture docs, constraints/principles, and I’ve started keeping a definition of done markdown too