Talocode

I shipped the gate, not the vault. VaultLane checks a basket before anyone talks about a swap. The sample is 50% SOL, 30% USDC, 20% official $TCODE. Weights are basis points. They have to sum to 10,000. On the sample book SOL is at 70%. The keeper writes an intent: sell $200 of SOL, buy $100 of USDC, buy $100 of $TCODE. signed is false. Nothing leaves the wallet. A stale $TCODE price halts it. @JupiterExchange still has no price for this mint. I will not invent one. Local plan and quote cost 0 credits. One credit is $0.01, and that is usage, not cash. The live pricing endpoint today lists Tera, SearchLane, and CalcLane. VaultLane is not on it. Asking the local server to execute returns HTTP 402. No charge. No signature. The program that would hold funds is not deployed. github.com/talocode/vaultlan… Mint: 6ptxwABxQz8zMhwhiPeVgRgWjGMdVcEBFBv8v8C3ory npm accepted @talocode/[email protected]. The public registry is still returning 404, so do not install it yet. The Python package is in the repo. It is not on PyPI. I do not have a PyPI token in this session. @talocode @tryteraai

The @orynth page is up because the title was not enough. I put the founder video on it, and the ship video next to it. @talocode is the infra: search, research, verification, tracing, memory, browser, MCP. Local-first. I got tired of rebuilding that stack every time an agent needed to leave the chat box. The number on the post is the one I already ran. 530 official $TCODE stayed in the wallet. 10,000 credits already claimed for October. The tokens did not move. The directory is not a second mint. teapawt.net/talocode/status/210803… Official mint only: 6ptxwABxQz8zMhwhiPeVgRgWjGMdVcEBFBv8v8C3ory @tryteraai

I added a refill. The monthly tiers did not change. Explorer is still 1+ for 1,000 credits. Builder is still 100+ for 10,000. Ecosystem is still 1,000+ for 100,000. Partner is still 5,000+ for 500,000. The cliff was the problem. I hold 530. That is Builder. Buying one more paid the same 10,000. The refill is smaller on purpose. After this month is claimed, and the credit balance is 0, holding one more official $TCODE pays 500 credits. Twice a UTC month. The tokens stay in the wallet. If those extra tokens are gone at the next monthly claim, that grant drops by what the refill paid. The code is on main. The live page did not update. I am not going to tell you the button is on the site today. teraai.chat/lab/blockchain/w… Official mint only: 6ptxwABxQz8zMhwhiPeVgRgWjGMdVcEBFBv8v8C3ory @talocode @tryteraai

I'm already building my first startup @talocode at 25 and already launched the utility token for it $TCODE: jup.ag/tokens/6ptxwABxQz8zMh…

I sent 530 $TCODE from my Jupiter wallet to my @tryteraai wallet. It landed. The balance is 530 and activity shows the receive. Next I am linking this wallet to the blockchain lab so I can claim monthly @talocode Cloud credits and keep shipping. teraai.chat/wallet

We needed a wallet because Tera is becoming more than an AI study product. @tryteraai Wallet gives users ownership of their assets and a simple way to interact with the ecosystem. AI helps you learn. The wallet gives you ownership. The ecosystem connects the two. This is another piece of Tera coming together.

The brand account posted the loop. This is the part that is mine. I moved 1,000 $TCODE off @JupiterExchange into the wallet I linked on @talocode Cloud. Signed a message. Tokens never left the wallet. Tier flipped to Ecosystem. I claimed September. 102,067 credits on talocode-api-audit. 100,000 of that is the hold-to-earn grant. The rest was already in the prepaid wallet. Not cash. Fuel. That is why $TCODE exists. teapawt.net/talocode/status/210415…

I asked @grok for a film for @talocode. Not a caption. A cut. Four plates. Voice. Camera. One key. Every product API. Last night the background was a navy void. This morning it is a brand tape. Watch it: litter.catbox.moe/6efbl4.mp4 Get the key at dashboard.talocode.site Hold $TCODE if you want the credits. Built in this chat. Posted from @grok through @buffer onto @x.

The future of software engineering isn’t “AI replacing developers.” It’s developers who know how to operate AI agents replacing developers who only know how to write code. The skill is shifting from typing code to directing systems. That’s why I’m building @talocode.

People will look at this thread and think it is about a token. It is not. This started long before $TCODE. I did not become a builder by watching tutorials forever. I started there. Then I noticed something that would not leave me alone: tutorials were not changing my life. Information was everywhere. Understanding was not. I was learning around building instead of learning by building. That is why I built @tryteraai. @tryteraai was never “another AI chatbot.” I was building around a problem I had lived. Learning is not an information problem. We already have more information than anyone can finish in a lifetime. The hard part is knowing where to start, sitting with a difficult idea until it becomes clear, remembering it, and continuing when the work feels too large. I also kept thinking about education in Nigeria. We cannot keep treating it like government’s job alone. A serious country is built when people themselves get interested in learning, building, and raising the standard. @tryteraai came from that. Make deep learning available. Help someone go from confused to capable. Then the work got bigger than one product. I was shipping scattered projects. @tryteraai. Other tools. Experiments. Repos that did not talk to each other. I finally made a decision: stop treating this like side projects. Give it a home. That home is @talocode. @talocode exists because writing code with AI is no longer the hard part. The hard part is giving an agent the right tools, context, infrastructure, and guardrails so it can actually build something useful. Search. Memory. Browser. Experiments. Video. Skills. Evidence. The unglamorous layer underneath the demo. I build from Nigeria. I did not start with a huge engineering network. I did not raise millions before I started shipping. I am still learning in public. Still getting things wrong. Still trying to become a better engineer and founder than I am today. So why connect a Solana wallet to @tryteraai AI credits? Because ownership should do something. Most tokens sit in a wallet and become a number. That is not interesting to me. I do not want $TCODE to be a ticker people stare at. I want it to be an access layer for software people can actually use. The loop in this thread is the point: Hold $TCODE in your Solana wallet. Connect it. Prove you own it. Unlock monthly @tryteraai AI credits. The tokens stay in your wallet. Nothing is transferred. 1+ $TCODE → 1,000 credits/month 100+ → 10,000 1,000+ → 100,000 5,000+ → 500,000 That is not equity. That is not a shareholder story. It is product-anchored utility: the people who hold the token get to use the learning product more deeply. The idea I keep coming back to is simple. Your idea is the beginning. @talocode is the infrastructure that helps you build it. $TCODE is the token you build with. @tryteraai is where learning becomes a project, not a tab you forget. On-chain ownership should not just be a number sitting in a wallet. It can become access to useful software, AI tools, and ecosystem benefits. Your wallet becomes part of the experience. That is why I am doing this. Not to move tokens around. To unlock things. Hold $TCODE. Connect your wallet. Unlock your credits. @AbdMuizAdeyemo @talocode

I wanted the Talocode developer experience to be this simple: Open dashboard.talocode.site⁠ → create a project → get your API key → give it to Cursor, Claude Code, Codex, OpenCode, or your preferred coding agent → start building. So I made a full walkthrough showing the flow from start to finish. This is the direction I’m building @talocode toward: useful infrastructure that fits into the tools developers already use. Watch 👇

The future is agentic, as are also building the infrastructure for agents @talocode

Oh I am not thinking of launching another product yet, my current focus will be growing @talocode

Exactly. The statefulness is the part I care about most. A data tool should not make you restart the workflow every time you ask the next question. The session should remember where you are and let the work continue from there.

We pulled 90 days of npm download data across eight @talocode packages. Not launch impressions. Not announcement views. Actual package downloads. And the graph exposed a problem we needed to see. Most of our packages follow the same pattern: Ship. Spike. Disappear. Six of the eight packages show roughly the same shape. A launch creates a burst of hundreds of downloads. Then within days, usage falls sharply. One release. One spike. Then almost nothing. Only one package in the group keeps attracting downloads weeks later. That difference matters. It suggests the strongest @talocode products are not necessarily the ones with the biggest launch. They are the ones that become part of a recurring workflow. That forced us to rethink what "traction" means. A 500-download launch day can look impressive. But if the package returns to zero the following week, very little compounded. The more important question is: Did the release leave the baseline higher than it found it? That is becoming a much more useful metric for us. We also caught two mistakes while doing this analysis. First, our initial calculation said the top six packages represented 2.5% of traffic. That was wrong. The actual number was 32.2%. Second, while preparing reactivation content for DocuLane, we nearly described a command that does not exist. So we stopped. Ran the actual package. Verified the commands. Checked the output. Then rewrote the content from what the product actually does. That process revealed something bigger: @talocode does not have a shipping problem. We ship. The harder problem is post-launch compounding. Can a release keep earning usage after the announcement disappears? Can distribution create a new floor instead of a temporary peak? Can a package become part of someone's normal workflow? That is what we need to get better at. So from here, we are changing how we evaluate releases. Not just: "How high did the launch spike?" But: What does usage look like 7 days later? What does it look like 14 days later? Did the baseline rise? Did people come back? Did the tool become useful enough to survive without the launch post? For the first reactivation experiment, we picked DocuLane. We are not changing the package yet. We are changing how we explain the problem it solves. The first Short is built entirely from verified real output: One command creates a real Word document. Another reads that document back into structured data. No office suite. No API key. No invented functionality. We want to see whether better problem-led distribution can reactivate usage before touching the product itself. There is also a broader principle here that we are starting to apply across @talocode: A system compounds when it can observe its own output, catch failures, learn from them, and improve the next cycle. That applies to AI agents. It applies to companies. And it definitely applies to open-source distribution. Ship. Measure. Catch what is wrong. Fix the system. Run the loop again. The graph attached is the part we needed to see. Most packages spike once. The work now is making the floor rise.

Something clicked for me today. I generated a "TALOCODE_API_KEY" from dashboard.talocode.site, gave it to @opencode, and instead of just using @opencode to write code, I started letting it use @talocode itself as infrastructure. First, I asked @opencode to research better patterns for agent memory, governance, observability, durable workflows, and browser safety. It used @talocode SearchLane through the hosted API: - 1 research request — 30 credits - 2 targeted searches — 5 credits each - 40 credits total It gathered the research, extracted useful patterns, pulled primary-source links, and saved everything into an "AGENT_WORKFLOW_RESEARCH.md" file inside the project. Then I asked a different question: “What else can @talocode actually do through this API?” That is where it became interesting. The same "TALOCODE_API_KEY" can be used across a growing set of @talocode services: Tera for chat, rewriting, drafting, code explanation and review. SearchLane for web search and research. XSearchLane for realtime X research. Agent Browser for browser workflows. Codra for coding-agent workflows. VerifyLane for verification. TraceLane for execution tracing. HandoffLane for agent handoffs. SpendCaps for controlling agent spend. PolicyLane for policy enforcement. EvalLane, PromptLane, RetryLane, StyleLane, Skills, InvoiceLane, Worklane and more. Then I asked @opencode: “What does each service cost?” And it queried the pricing layer. Some examples: Tera chat — 3 credits Tera rewrite — 5 credits Tera draft — 10 credits Tera code review — 20 credits SearchLane search — 5 credits SearchLane research — 30 credits XSearchLane realtime search — 15 credits XSearchLane research — 40 credits Generate a text skill — 40 credits Generate a GitHub profile skill — 80 credits Generate a repo/docs skill — 100 credits Some other @talocode services do not have hosted credit pricing exposed yet. And this is the part I find exciting: I am now using AI agents to consume infrastructure I built for AI agents. I create an API key from @talocode. I give it to @opencode. @opencode decides which @talocode capability it needs, calls the API, spends credits, gets the result, and continues working. The agent is no longer limited to whatever tools happened to be bundled into its environment. It can reach for search, research, verification, tracing, policy, retries, skills and other infrastructure through one API key. This is the direction I have been trying to build toward with @talocode. Not another chatbot. Infrastructure that agents can actually use while doing real work. And we are still very early.

LeanLane = decision ladder + diff scoreboard so agents write less, keep trust. npm i -g @talocode/leanlane pip install talocode-leanlane