Hi! its Subhan so I was confuse i was working on an hackathon in which i have to make an agent that can prove why did the deal go cold, with the help of data base find the clues arrange them and send it to the user, and also tells how u can win it back or prevent these kind of things. so due to some personal reasons i stopped but now i am thinking to continue and complete it. so I was confuse that should i do it or not. I would like to get your recomendations on whether I should continue with it, and if so, I’d love any tips on the best way to approach it effectively. and should i continue it or not. Thankyou! for your time.

Most examples here are for US businesses: roofers, real estate, dental clinics. I'm in Türkiye. If you sell in another country, what do local businesses pay for there? And did anything that works in the US fail in your country?

I have one Tavily key on the free tier, 1,000 credits a month, reset on the 1st. Claude Code, Codex and Hermes all use that same key. When sessions run in parallel they drain one pool, and none of them sees what the others spent. On 2026-09-15 I measured it: 786 credits across 113 calls. So a single Tavily MCP call costs several credits, not 1. The heavy calls are worse. A crawl is 100+ credits, and tavily_research can be anything from 4 to 250. So research is never called now without flagging the cost first. On 09-19 I moved whole-site and follow-links jobs to Scrapling, free and local. Tavily crawl/map is only the fallback now. The order is WebSearch, then Google in the browser pane, then Scrapling, then Tavily. One task gets at most ~3 Tavily escalations before it stops and says so. Scrapling has its limits too, measured the same day. Cloudflare-walled pages only pass with real_chrome=True, the bundled Chromium fails there. DataDome on ImmoScout24 stays closed. What I take from it: pick the tool that's most effective first, and the free one only when it's a tie. And measure what a metered call really costs before you budget around it. If you share one metered API key across several agents or tools, how do you track and cap what each of them spends?

By 10-29 the app listed 33 sessions. 30 of them were empty and dead. Every Mac runs its own `claude remote-control` agent, and the name carries the rank: `1 · M5 Max (my code)`, `2 · M1 (my code)`, `3 · Intel (my code)`. On the phone I tap the highest one that's online. I rejected an election between the Macs because it would cut a live session when a higher Mac woke. The pile came from startup. Each agent start pre-created an empty session, and KeepAlive restarts the agent after every sleep or Wi-Fi drop. First fix: run the agent with `--no-create-session-in-dir`. The script adds the flag only where the CLI knows it. The Intel is on 2.1.284, which doesn't, so it keeps its single `3 · Intel` session. Since 2026-10-30 a job also archives disconnected sessions when they're ≥48 h old with zero user events, or when their `environment_id` answers 404. Every remote-control start makes a new environment and deletes the old one, so a 404 session can't be reached again. Before archiving one, the job saves the transcript (.md plus raw .json), and if that save fails it doesn't archive. Sessions with an empty `environment_id` are desktop-app ones and never touched. At most 60 per run, there's `--dry-run`, and archived sessions can be unarchived. First run: 7 env-gone sessions archived, 0 empty ones. Lesson for me: a KeepAlive agent repeats whatever it does at startup on every restart. If you run long-lived remote-control agents that restart on sleep or network drops, how do you keep dead sessions from piling up?

My second brain is plain markdown: one file per project, tied together by a router file and a STATE file. To keep it in check I added a lint that gives every file a word budget. If a file stays over budget for 7 days, the warning becomes an error. My fix right now is a split. The over-budget part moves into its own file that opens with a "read this only when" line, and the router gets a line pointing to it. That way a session only opens what the task actually needs. I'm curious whether that's the right long-term move. How do you keep yours from growing forever? Do you split like this, archive old stuff, summarise it, or just let search handle it? And if you've switched approaches, what made you drop the first one?