Cut your LLM token bill by 87%, plus three more tools worth your time
This week kept circling back to one question: what does it actually cost to run an AI agent, and who's doing something about it? Three of the four tools below are different answers. headroom is the one I keep thinking about. It sits in front of your LLM calls and strips the junk out of everything your agent reads (logs, tool output, RAG chunks, file dumps) before it ever hits the prompt. The reported numbers hold up: 87% fewer tokens on a log-search test, accuracy unchanged. One command to install, runs entirely on your machine, nothing leaves your laptop. If you're running coding agents hard, it pays for itself almost immediately. The rest follow the same instinct: own your stack, control your costs. DeepSeek-Reasonix is a terminal coding agent built around prefix caching, so a session that would run sixty dollars comes in closer to twelve. Hermes WebUI gives you a self-hosted agent with memory that isn't chained to ChatGPT or Claude.ai. And Twenty is the outlier, a Salesforce replacement that actually looks like it was built this decade. Four tools, one theme: keep your data and your bill under your own roof.
The Context Optimization Layer for LLM Applications
The Lens
headroom strips boilerplate from everything an LLM agent reads (tool outputs, logs, RAG chunks, file dumps) before the content hits the prompt. The reported numbers are real: 87% fewer tokens on a 100-log needle-in-haystack test, 92% on code search results, with accuracy unchanged on GSM8K and TruthfulQA. Apache 2.0, runs entirely on your machine. Setup is one command. `headroom wrap claude` or `headroom wrap codex` puts it in front of the API call. There is also a Python and TypeScript SDK for direct `compress(messages)` use, plus a proxy mode for everything else. Local-first design means no data egress, and compression latency is milliseconds, not a network hop. If you are paying for Claude, GPT, or Sonnet at scale, this pays for itself fast. Token costs drop directly. The hosted dashboard at headroomlabs.ai is a community leaderboard, not gated functionality. Solo developers running coding agents heavily: install it. Teams burning through enterprise LLM budgets: pilot on one team first. The catch: aggressive compression on novel content can lose nuance the model needed. The reversible design lets the model pull original bytes back via tool call, but that only works if the agent is configured to use it. Verify on your real workload before trusting blanket compression.
DeepSeek-native AI coding agent for your terminal. Engineered around prefix-cache stability — leave it running.
The Lens
DeepSeek-Reasonix is a coding agent that lives in your terminal and runs on DeepSeek's models. It edits files, runs shell commands, plans multi-step changes, and plugs into MCP servers and custom skills, the same shape as Aider or Claude Code but built specifically around DeepSeek. The agent itself is free and MIT licensed; you bring your own DeepSeek API key. The whole point is cost control through prefix caching. The project is engineered to keep your conversation prefix stable so DeepSeek's cache keeps hitting, and the numbers are real: one documented session ran about twelve dollars instead of sixty-one without caching. Install is a single npm install with Node 22 or newer. A Tauri desktop client exists but it is still a prerelease, so the command line is where the stable experience lives. Solo developers already paying for DeepSeek API access get a capable agent for nothing extra. Small teams that want AI coding without per-seat Copilot or Cursor bills can run this and pay only for tokens. Larger teams will weigh the lack of polish and support against the savings, and many will still want an IDE-integrated tool instead. The catch is that you are tied to one model family. DeepSeek is cheap and capable, but it is not the strongest coding model out there, and the project says so itself. If you need the best results regardless of cost, this is not it.
Hermes WebUI: The best way to use Hermes Agent from the web or from your phone!
The Lens
Hermes WebUI is a browser frontend for Hermes Agent, a self-hosted autonomous AI agent that holds memory across sessions, runs scheduled jobs, and integrates with messaging platforms. Free and MIT-licensed. Setup is moderate. You bring your own LLM API key (OpenAI, Anthropic, Google, DeepSeek, OpenRouter, others) and run the agent plus WebUI on your own hardware or VPS. Once running, the agent persists conversation context, learns from interactions, and can be triggered on a schedule. The web UI mirrors the CLI experience without locking you out when you close the terminal. For solo developers and small teams who want an AI agent that isn't tied to ChatGPT or Claude.ai, this is a real option. Your conversations, your memory, your hardware. The cost is your LLM API bill, which can climb fast if the agent is making frequent calls. Solo: probably $10 to $50 per month in API spend depending on usage. The catch is that "autonomous AI agent" is doing a lot of work in the description. These systems still hallucinate, still drift, still need supervision. Don't wire it into anything destructive without guardrails.
Building a modern alternative to Salesforce, powered by the community.
The Lens
Twenty is a full-blown CRM built to replace Salesforce. Not a toy. Not a contact list with delusions of grandeur. It handles custom objects, kanban views, email integration, calendar sync, workflow automation, and role-based permissions. The UI borrows from Notion and Linear: clean, fast, modern. Self-hosting runs on Docker with Postgres and Redis. The community is massive and active. You get custom fields, API access, and webhooks on every tier. The AGPL license means the core stays open. Enterprise features like SSO sit behind a commercial license. At $9/user/month for cloud, the open source tax on ops might make the hosted version the smarter call anyway. Alternatives like SuiteCRM and EspoCRM exist but feel dated by comparison. Twenty looks and feels like a product built in 2025, not 2005. The catch: self-hosting requires Postgres plus Redis plus the app server. That is not a weekend project for a solo founder.
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