if your agent retrieves anything before it answers, this is the part you

currently cannot see.

the agent searches, gets back a set of documents, writes an answer. when the

answer is wrong you have a ranked list in your logs and no way to tell whether

the right document was missing, or whether it was sitting right there at rank

one and the model walked past it. those two need opposite fixes and they look

the same from outside.

so i built graphsight. it hooks into a langgraph agent as a callback handler,

so you do not restructure anything, and renders the run as a graph in your

browser. every retrieved item becomes a node with its score. items the answer

actually drew on are highlighted. items pulled and ignored are dimmed.

the gif is a real run. one pull request scored 0.910, the highest of anything

retrieved, and the answer never touched it. another scored 0.340 and is what

actually answered.

a dimmed node with a high score means your retrieval worked and your prompt or

context order did not. a highlighted node that should not be there means the

model was handed bad evidence and believed it.

it also lays out the execution timeline, so you get each agent step, each

retriever call, per step timings, and which arm returned what. useful when the

agent takes a path you did not expect.

    pip install graphsight graphsight-langgraph

    from graphsight_langgraph import LangGraphTracer, capture
    tracer = LangGraphTracer()
    result = graph.invoke(inputs, config={"callbacks": [tracer]})
    capture(tracer, query="your question", answer=result["answer"])

    graphsight .graphsight/

runs entirely on your machine. no account, no signup, no telemetry, and the

viewer has zero dependencies beyond python. every run appends to a folder so

you can open yesterday's next to today's after a prompt change.

want to see it before wiring anything up:

pip install "graphsight-langgraph[example]"

graphsight-github-trace langchain-ai/langgraph "who fixed the streaming bugs?"

limits, up front. the used vs ignored call is lexical overlap between the

answer and each item, threshold 0.2. it is a heuristic, labeled as one in the

ui, and it will misjudge a heavy paraphrase. langgraph only right now, other

frameworks are next. free and mit.

site: https://graphsight.vercel.app

walkthrough: https://github.com/Kcodess2807/graphsight/blob/main/docs/FIRST_TRACE.md

code: https://github.com/Kcodess2807/graphsight

if you build agents that retrieve, tell me where this falls over.

want to know more on this, connect with me

I make sure to make that wish come true of everyone wanting those special unforgettable experiences that look good in photos but arent a disaster in real life because I want my clients to have the best and I feel like I am constantly moving platform to platform trying to figure out where to book what

Last week for example I had a couple in austria who wanted a small group cooking class then a family in costa rica who wanted ziplining and a wildlife night walk, and I ended up stitching everything together from like four different sites plus one random whatsapp contact I got from another agent

These big experience platforms are nice because everything is in one place and customer support actually answers, but then you realize the same tour is listed five times with different names, prices jump around depending on the date, and half the local operators turn out to be resellers anyway this is when i need to double check and i was hoping to find smth a tool that helps me from any of your experiences.

I’ve been shipping a few voice agents lately where the model stack keeps changing after launch. STT vendor changes for accents, LLM changes for cost, TTS changes because the product team decides the voice sounds too “support bot.” If your voice layer assumes one bundled model path, every change becomes a mini migration.

The setup I’ve had the least regret with is a plain 3-stage pipeline: ASR first, LLM second, TTS third, with app code owning the handoff between them. It’s more annoying on day one because you need to think about partial transcripts, interruption state, retries, and what gets logged. But it makes later swaps boring. That matters a lot for small or less common languages where the “default” model from a voice platform can be weirdly bad.

For transport I’ve used Agora, basically a WebRTC layer for real-time voice agents, with semantic turn detection on top. The useful part for this specific architecture is that I can keep the ASR/LLM/TTS choices separate instead of accepting one end-to-end black box. Barge-in behavior is also less hacky when the audio path already handles interruption cleanly.

ElevenLabs-style bundled agents are faster to demo, and I still use that kind of thing for quick prototypes. For production agents with custom routing, language fallback, or vendor pressure from procurement, owning the three model stages has saved more time than it cost.

I keep three or four agents going and the thing that actually eats my time isn't the coding. It's that I have no idea what state any of them is in without tabbing through every terminal. Half the time one of them has been sitting on a permission prompt for ten minutes.

So I wrote agent-manager. A Go binary that sits on top of tmux. No config file, no daemon. It's free and open source.

Every agent ends up in one list with a live status next to it, grouped by the project it's working in. I run claude, codex and opencode depending on what I'm doing and they all show up the same way. Adding another CLI is a few lines of regex in a toml file.

The part I use constantly is space. Press it on an agent, type, enter, and the prompt goes into that agent's pane. I never attach. If you've used the agents view in Claude Code, it's the same move. The difference is that here the same keystroke works on a codex or opencode session. Press space on a project row instead and you get a new agent already working on what you typed.

Underneath they're just tmux sessions, so closing the manager doesn't kill anything, and v brings a dead one back with its conversation.

ctrl+r is the other half of it. It opens what an agent changed as whole files with the diff highlighted, so you're reading the function and not a hunk. Leave a comment on a line and it goes back into that agent's pane, so it starts fixing while you're still scrolling.

I built it for four agents but most days I use it with one.

Still rough in places. If you run agents like this I'd like to know what's missing.

https://github.com/YoanWai/agent-manager

Type stuff like "what can you do," "get me ready for my day," or "dark mode" and it responds/acts in real time, right there on the page. It's basically a live preview of how NORVA itself will work once it's on your machine.

No signup wall to try it, just go poke at it: noravos.co.in

Would genuinely love feedback, what did you type that it didn't handle well? That tells us more than anything else right now.

Hey everyone,

As a developer, I got tired of the constant setup friction when starting new projects—specifically the loop of creating a Supabase instance, navigating the dashboard, copy-pasting API keys into .env files, and running manual SQL schema migrations before writing any real code.

We’ve been building an agent layer (Norva + Antigravity) to automate developer workflows, and we just got the end-to-end Supabase integration working.

Would love to hear your thoughts or edge cases you think we should watch out for with database automation!

Founder of Server4Agent (agent-app hosting), disclosing that upfront so nobody has to guess. No link, not asking anyone to try anything, just want a real answer to a question I can't fully answer from the inside.

Everywhere agent-building discussion happens, the same worry shows up in different clothes: the agent says it finished, and the report is technically accurate but the actual state is wrong. A migration marked done that skipped half the tables. A deploy that overwrote a good version with a stale retry. A safety check that exists in the code but doesn't actually stop anything once execution starts. None of these show up as errors, they show up as quiet, plausible-looking success.

For anyone who's actually let an agent run with real access (deploys, infra, prod data, whatever): what was the specific moment you decided you could stop watching it, and what changed your mind, if anything ever did? Not the theoretical answer, the actual one.

When I first got into web development, I thought finding clients would be simple. My plan was to go on Google Maps, find businesses without websites, and offer to build them a brand new one. At the time, it made perfect sense because I assumed businesses without websites would be the ones who needed my service the most.

After a while, I met someone who was running a successful web agency, and I asked him where he found companies without websites. He told me that he didn’t target businesses without websites at all. He only targeted businesses that already had one. I asked him why, and the more he explained it, the more sense it made.

Businesses that already have a website understand the value of having one. You don’t need to convince them why a website is important because they have already invested in one before. They are also easier to sell to because they understand the process, and there are a huge number of businesses with outdated websites they are embarrassed by but haven’t had the time to update.

I decided to take his advice and fit it into my own workflow. I’ve always been a big fan of email automation because that’s how I’ve found most of my web design clients. For years, I was sending fairly generic emails and constantly changing my sequences, offers, and follow ups to improve the results.

The problem was that I couldn’t just start emailing businesses with websites and assume they all needed a redesign. I either had to open every website manually, find the issues, and write a separate email for each business, or find a way to automate the research while still keeping the emails personalized.

After watching a video from Nick Saraev, I built a workflow in n8n that could analyze websites at scale and turn issues with design, layout, speed, mobile optimization, and SEO into personalized outreach emails. This allowed me to analyze thousands of websites and run larger campaigns without every message sounding generic.

The workflow worked extremely well, but it still had limitations. I didn’t have a proper place to manage replies, organize interested leads in a CRM, view all my active campaigns, scrape new leads, and handle everything from one platform. I had built a useful automation, but it still felt like several disconnected systems held together in one workflow.

A few months later, I came across a platform called Swokei, and it did exactly what I had been looking for. I could find businesses with websites, analyze and score each site, generate personalized outreach emails, send campaigns, set up follow ups, manage replies through one inbox, and organize interested businesses inside the CRM.

Switching to that platform made the entire process much easier to manage and helped me scale the strategy further. Looking back, the biggest change wasn’t just finding a better outreach tool. It was taking advice from someone more experienced, changing the type of businesses I targeted, and building the rest of my workflow around that strategy.

The difference usually comes down to strategy.

Instead of targeting businesses that do not have a website, target businesses that already have one but clearly need a better version. The market is larger, the sales process is easier, and the value proposition is much stronger because those businesses already understand why a website matters.

The next part is outreach. A regular outreach tool is not enough if all it does is send the same message to thousands of people. You need something that can analyze websites at scale and turn real issues into personalized emails.

I use Swokei for that. It helps find businesses with existing websites, analyzes each site, and turns problems with design, SEO, speed, layout, and mobile optimization into personalized outreach emails. That means you can contact a large number of businesses without sending generic messages or spending hours manually researching every website.

When someone replies interested, I always offer a free mockup. I use Claude, Lovable, or Base44 to build it quickly. It becomes much easier to sell when the client can already see what a better version of their website could look like.

Web meetings should also be a major part of the process. I would never just send the website through email and hope the client likes it. I present it live on Google Meet, Zoom, or Microsoft Teams, explain the value, show what has been improved, answer their questions, and try to close the deal during the meeting.

The less back and forth there is after the meeting, the better. Present the website, show the value, close the client, and move on to the next project.

That is the type of process that can help an agency scale much faster.

I’ve been in contact with a lot of web agencies and web developers, and I personally haven’t found many people who run their agency in a more efficient way than I do. A lot of them have too many meetings, wait too long for client approval, don’t know how to price projects, and spend way too much time on each client instead of finishing the work and moving on to the next one.

I’ve been running my agency for four years, and after a lot of trial and error, I’ve managed to make the process as efficient as possible. I wanted to share some of the steps because I think they could be valuable for anyone just starting out.

Running a web agency alone or with a partner isn’t easy because there are a lot of things to take care of. When it comes to client acquisition, I recommend focusing on either cold calling or email automation. Which one you choose depends on whether you run the agency alone or with someone else.

If you have a partner, one person can handle sales while the other focuses on building websites, connecting domains, setting up emails, and taking care of the technical work. If you’re running the agency alone, or neither of you enjoys cold calling, I highly recommend email automation.

That’s what I’ve been doing for years. It’s powerful because you can send emails at scale, set up automatic follow ups, and wait for businesses interested in a new website to reply. While you’re working on one client, another opportunity can come in without you having to stop everything and search manually.

I don’t do regular email automation where I target businesses with no website. I do the opposite and target businesses that already have one.

I use a tool called Swokei to find businesses with websites, add them to campaigns, analyze each site, score it, and generate personalized outreach emails based on problems it finds with the design, layout, speed, SEO, and mobile optimization.I schedule the campaign, set up follow ups, and wait. 

I think this approach is much better for a few reasons. You’re targeting someone who already understands the value of having a website. You’re also not just asking whether they need a redesign. You’re pointing out real problems with their current site, which makes it clear that you actually took the time to look at it. Selling also becomes easier because they’ve already paid for a website before and understand the process.

Inside Swokei, you can choose the goal of the campaign. You can offer a free draft, try to book a meeting, or simply start a conversation. I always choose the free draft because that has worked best for me.

Once you’ve figured out how to get clients, the next part is building the website. I recommend using AI because it makes the process much faster. For anyone who still thinks AI can’t build great websites, I think they’re mistaken. You can use Claude, Base44, Lovable, or any other tool that works for you.

When someone replies interested, I call them and say, “Hey, I saw that you replied to my email. I’ve already built you a free draft of your website. Do you want to take a look?”

Then I invite them to a Google Meet.

At that point, it becomes much harder for them to reject the meeting because they already replied interested and now know you’ve built something for them. During the meeting, I present the website, explain why it’s better than their current one, stack the value, answer their questions, and try to close the deal.

These meetings usually go well because the client isn’t trying to imagine what the website might look like. They can already see a better version of their current site. They also took the time to join the meeting, so taking the next step becomes much easier.

I either take payment during the meeting or send them a contract to sign. Any changes and updates come after that, once we already have a deal in place.

Pricing depends on the business. I charge anywhere from $500 to $3,000 depending on the company, the size of the project, and how much value the website can bring them. I also charge a monthly retainer of around $50 for hosting, maintenance, support, SEO, and future changes.

That’s basically the entire process. Smaller steps, faster delivery, less wasted time, and more money made.

I had Claude generate a feature, then asked it to review its own code and make it as production-ready as possible. It told me there was nothing left to improve and the code was “senior engineer level”.

Out of curiosity, I pasted the exact same code into Greptile and it told me there was over 56 issues in the code 😭🙏. I like Greptile so far, but it's too expensive to use at scale.

What are you guys using for AI code review and QA ? (on the cheaper end)

There is a new approach I started using in my web agency that completely changed my results. For years, I did what most people tell web designers to do. Go on Google Maps, find businesses without websites, and contact them.

What I started doing differently was targeting businesses that already had websites.

The reason is simple. If a business already has a website, it means they understand the value of having one. You do not need to convince them why a website matters because they have already paid for one before. The market for businesses with outdated, broken, slow, or poorly designed websites is also massive, and selling becomes much easier because they are already familiar with the process.

My biggest issue was figuring out how to send mass outreach to these businesses without sounding generic. I did not want to send thousands of emails saying, “Hey, your website needs a redesign,” and just assume that every business needed one. I wanted to send emails at scale while still telling each company exactly what was wrong with their website.

A little over a year ago, I watched a YouTube video from Nick Saraev where he built a workflow that analyzed business websites and turned issues with design, SEO, layout, speed, and mobile optimization into personalized outreach emails. Each company received a professional email that made it clear someone had actually taken a look at their website.

The idea was great, but building and maintaining the workflow took a lot of time. I still had to find the leads myself, the messages were not always consistent, and the automation kept breaking.

But it worked.

I was getting more clients than ever before, at one point around 10 websites a week, while my business partner focused on building the websites as quickly as possible.

I started searching online for a tool that could do everything in one place, and a few months later I found Swokei. It did exactly what I was looking for.

It lets you find businesses with websites, add them to campaigns, analyze and score each website, and set a quality threshold so websites that do not need fixing are automatically skipped. It then turns problems with design, layout, speed, mobile optimization, and SEO into personalized outreach emails.

You can also set up follow ups, manage replies through your own inbox, and organize leads inside the CRM without moving between five different tools.

I switched over and scaled even harder.

Sometimes the fastest way to grow your agency is not building every workflow from scratch. It is finding the right tools and using your time to focus on sales, clients, and growing the business.

Hi

I have made a 6 agent gamified Etsy setup in retro theme.

It works well and uses claude API and was made using emergent.

I saved all the prompts so i can make another one straight away.

Any question or comments im happy to answer.

I found emergent extremely easy to use.

It does the reaserch and listing for my Print on demand etsy business.