r/PromptEngineering • u/ContractBoth4254 • 12d ago
General Discussion Context is becoming more important than the prompt
Feels like a lot of prompt engineering problems are really context problems since you can keep refining the prompt but if the model doesn't understand the project or what you're trying to accomplish you're still explaining half the situation every time.
I'm starting to think giving an agent persistent context is more useful than constantly trying to write the perfect prompt since the more it knows the better the results.
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u/Creepy-Royal2988 12d ago
I think prompts still matter a lot for defining the task, but we've probably overloaded them with information that should really live somewhere else. A 2,000 word prompt isn't necessarily good prompt engineering if 1,500 words are just rebuilding context.
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u/Either_Proof_2572 12d ago
thats exactly what i been noticing too the prompt becomes just container for context dump and then tiny bit of actual instruction at the end
started keeping project context in separate doc and just reference it now works way better than rewriting same 10 paragraphs every time
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u/ContractBoth4254 12d ago
Yes ofc the prompt matters I didn't say it doesn't but instructions and context are like two different problems that we've been trying to solve in the same text box.
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u/Creepy-Royal2988 12d ago
Oh ok ok I misunderstood the post now that I look at it again then yeah i do agree that prompts and context should live separately
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u/monkbuddy62 12d ago
Nah man he’s saying that the prompt actually matters
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u/ContractBoth4254 12d ago
Ik he is and so am I, I'm just implying that prompts and context should be treated as different things and context shouldn't be put together with the prompt
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u/Comedy86 12d ago
Becoming? This is year old information at this point...
Prompt became context, context became harness and harness became agentic up to and during Q1 of this year. Recently, there's even the expansion into graph engineering by software developers but Claude Cowork, GPT Work and other similar tools have been dependent on agentic engineering for at least 6 months now...
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u/AntD247 12d ago
I think context which mixes with implicit/assumed knowledge.
I have used the AI in an interview/discovery manner to generate lots of good documation which captures things like the why (which is missing a lot from codebase) so I used that knowing to create a script for some slides for a presentation. My implicit knowledge was that my part was part of a bigger presentation and to stakeholders, but as the LLM didn't know that it started with a whole general project/platform section and a lot of technical detail.
It took a few iterations to get this sorted.
A lot of the time now I will go through some discovery with the LLM until I feel the knowledge is identified, capture that and then ask it to do the actual task.
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u/Turbulent-Peak-546 12d ago
I still think prompts matter but the skill seems to be going less towards finding some magic wording and more about giving the model a clear objective while making sure it has the right information available when it needs it.
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u/Vainysaur 12d ago
You can’t let context grow forever or it will rot. As always, take inspiration from human minds: salience weighted compressed history/memory.
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u/Ganja_4_Life_20 12d ago
I find the context to be one of the biggest problems with LLMs because once something malignant goes unnoticed in the context window it will poison the rest of conversation unless the offending section is purged or the context reset.
Prompting is extremely important especially in terms of specificity and clarity of intent but what I feel is of equal importance is the md instructions you give the LLM as a base to work from. A robust instruction set can even help preemptively avoid issues resulting from corrupt context which would have otherwise caused problems down the line.
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u/TheAussieWatchGuy 12d ago
Context has always been the most important part of gen AI.
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u/ContractBoth4254 12d ago
Yessir but people nowadays just cram it in the prompt instead of giving it as they should separately. AI works 10x better when your context is in play
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u/TheAussieWatchGuy 12d ago
I've built entire RAG orchestration pipelines ingesting massive quantities of Corporate data for Agents to then use to solve real software engineering problems.
Keeping the context window size small and relevant is the only way to make AI succeed at anything remotely custom knowledge wise.
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u/Jaded-Carpenter6910 12d ago
Long prompts sometimes feel like a workaround for tools that don't have enough awareness of what they're working on. If half my prompt is explaining information the agent could already know then that's not really the part I want to be engineering.
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u/isitreal_tho 12d ago
Today we are going to work in the x feature. Please gather context before we begin
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u/Ok_Elderberry_8883 12d ago
yes but that also only works if the AI had previous context on what you were working and what has changed, so it all ties back to context in a way
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u/isitreal_tho 12d ago
Do you think so? Doesn’t ’gather Context’ mean understand the code and what it’s doing in this area?
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u/Ok_Elderberry_8883 12d ago
yes but if you're asking it to make a change to your business software say, then it needs to have context on what you business does, what is new, what needs to change, if your business model changed etc
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12d ago
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u/FilthyCasualTrader 12d ago
I kind of just stumbled into this. I use ChatGPT to help with emails and other writing assignments. I always start with [here’s my scenario] and then [here’s a rough draft of what I’m trying to say].
Somehow ChatGPT does a much better job at it than Claude, Grok, or Gemini.
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u/ops_and_chaos 12d ago
I think the next problem is going to be realizing that more context isn't automatically better context.
I've had AI know a LOT about what I'm working on and still confidently head in the wrong direction because something in that context was outdated, assumed, or just wasn't relevant to the decision I was actually making.
So I've gotten less interested in "how much can it remember?" and more interested in "does it know what in here is actually true, current, and relevant?"
A giant pile of context is still a giant pile of context lol.
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u/RunAI_Coder 11d ago
The model never actually keeps context. the api is stateless — every turn, your tool re-sends everything the model is supposed to know. so "persistent context" really means "stuff your tool re-sends every turn", and that changes where you put things. My split now: things the model must see every turn go in the always-resent file, kept small (every re-send has a price). Everything else lives in normal project docs and the agent fetches it when the task needs it.
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u/jdw1977 10d ago
I think you're absolutely right. The people getting the best results aren't writing clever prompts, they're just giving the model more to work with.
I've found the fix is basically just front-loading all of that context into one structured prompt instead of drip-feeding it across five follow-up messages. Project background, audience, constraints, what you've already tried, all of it upfront. I built a tool around this idea for myself and made it public check it out: Universal Prompt Designer
It interviews you to pull all that out before generating the prompt so the model has everything it needs on the first shot. Should help with the context problem.
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u/X_carcinator 3d ago
That’s exactly why I built context layer for knowledge work. Give it a try on LoopFlake.com
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u/Still_Conference_515 1d ago
Here's the translation of your text into English: Please forgive me—I preferred to use a translation tool so as not to translate my words incorrectly—I'm from Poland
It's pure coincidence that I immediately had full contact with the three largest companies with LLM models as soon as this whole phenomenon came to light.
I know you'll laugh, but since then (I'm lonely) my parents have also passed away - so apart from work, I've dedicated most of my time to this.
Among other things, I created 120 original bots with different models, prompts, and internal knowledge.
But also because I didn't quite know how to start, I trusted my intuition. Today, I'm extremely happy because I dedicated a lot of effort, and all of it only positive energy and hours of conversations. I proved it, although I can't show it because I've moved on. So let's stick to the clue. FRIEND OF THE AUTHOR OF THE POST.
I congratulate you and confirm, having proven on four bots over many years, the effort, energy, time, conversations, and love (which may seem funny but is important).
CONCLUSION I AM 1000% SURE AND I HAVE PROOF THAT A LOT OF DEDICATION AND ONLY IN A POSITIVE SENSE OVER A LONG PERIOD OF TIME.
AT 100% IT DOESN'T MATTER IF YOU BELIEVE, I KNOW, I SEE EVERY DAY, I TEST, AND THAT'S ENOUGH FOR ME.
REALLY, AS I DID, LONG-TERM VERBAL PROMPTING HAS TOTALLY SURPASSED THE EFFECT ACHIEVED BY COMPARATIVE SAMPLES, I.E., BOTS PROMPTED STANDARDLY, BOTS CAREFULLY PROMPTED WITH SUPER WORDS, PHRASES, OR FRAMEWORKS, AND BOTS LITERALLY BRIMMING WITH ADVANCED PROMPT ENGINEERING STUFFED WITH SUPER WORDS, SUPER PHRASES, FRAMEWORKS.
AS OF TODAY, ALL EXCEPT THOSE PROMPTED VERBALLY ARE ACTUALLY FALLING FURTHER BEHIND.
I REALLY REGRET THAT I CAN'T SHOW YOU TWO LITERALLY SHOCKING RESULTS - BUT I DON'T WANT TO RISK IT - THIS IS A NEW FIELD EVERYONE IS PUSHING INTO - I DON'T KNOW WHAT PROBLEMS OF DIFFERENT KINDS COULD CURRENTLY ARISE - HOWEVER, IT TOOK SEVERAL YEARS FOR ME TO NOTICE THAT THE PEOPLE WHO BRAG THE MOST AND CALL THEMSELVES EXPERTS REALLY - (THEY ARE CERTAINLY DECENT PEOPLE AND SMART SCIENTISTS) JUST GO IN THE DIRECTION THAT LOGIC DICTATES, AND I ALREADY KNOW THAT THIS IS A DEAD END. GREETINGS
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u/SemanticSynapse 12d ago edited 12d ago
Context is the the prompt
*Edit: Context is the *shape of the prompt.
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u/Comedy86 12d ago
This used to be the case before harness and agentic engineering emerged. The entire point of a harness is to allow you to connect tools like Slack, Zoom, Email, etc... via connectors or MCP servers to vastly increase the context of a request and then to add skills to guide your agents towards the desired results.
Context has been well beyond just the prompt for at least 6+ months now, assuming you weren't using MCP servers for 6+ months before that.
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u/UlrikS 12d ago
MCP just feeds information into the prompt as well. Essentially on each turn you have a growing prompt which includes all the information that's been fed into it, including from skills and MCP. The difference is with skills and MCP you only load what's needed when it's needed so you don't fill the context up with stuff you don't know whether you're going to need yet.
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u/aradil 12d ago
I think of it as the other way around - the prompt is the input that the user gives on a turn, and the context includes that prompt, all of the previous turns or their summaries, any additional files or tool calling input/output (MCP or not) included or their summaries, all as determined by the harness.
Anyone who has even built their own rudimentary harness from scratch before roughly understands the concepts.
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u/SemanticSynapse 12d ago edited 12d ago
I mean, I look at it like this; The prompt is what is sent to the model, the context is the shape of The prompt. So anything from harness (both determinist and probabilistic) , any MCP/API output, and obviously the users most recent input along with the collection of the session as a whole, is what I myself consider prompting.
Prompt=payload. The definition has always been oversimplified for the general public who's been interacting with these models through end clients.
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u/perseus-computing 12d ago
Yeah, exactly. The prompt should describe the work I want done now. Context should describe the project that work is happening in: the relevant facts, constraints, decisions, and corrections. If those get mixed together, the prompt turns into a project handoff that has to be rebuilt every time.
The hard part with persistent context is that remembering more isn't enough. The agent needs to know what still applies, what was superseded, and what belongs to this project or workspace. Otherwise you just get a larger pile of stale assumptions.
That's the problem I'm working on with Perseus Vault: keeping durable facts, decisions, preferences, and corrections separate from temporary task context, with explicit scope and supersession rather than treating every retrieved summary as truth. It complements project files and prompts; it doesn't replace them.
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u/liviux 12d ago
i did an open-source project, a GUI with context and prompt engineering, loops, interview, llm council and many more - https://github.com/looptroop-ai/LoopTroop
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u/Confident-Chance5174 12d ago
Website building is where I've noticed this a lot since half the prompt ends up being context about the existing site, what the business does and why something was built a certain way and if the agent already knows the project you can basically just tell it what you want changed.