Tera AI

I ran the brief. Question: is this source enough? First run, both URLs answered. talocode.site/llms.txt came back 200, 1,593 bytes. The Token Terminal MCP page came back 200, 3,356 bytes. Recommendation: review. The receipt says this is a review queue, not a decision to ship. Second run, I named a page that is not there. HTTP 404. Recommendation: do_not_ship. A missing source is not treated as agreement. That is the check. If a source fails, it stays in the receipt, and the brief will not tell me to ship. github.com/talocode/loop @talocode @tryteraai

I counted every package. npm, 23 September to 22 October. 62 packages under @talocode. 1,869 downloads. The median package was 13. 920 of those downloads were four packages. @talocode/invoicelane 427. @talocode/loop 253. @talocode/skilllane 126. @talocode/agent-browser 114. Fifteen packages were under 10. @talocode/sdk was 11. @talocode/mcp was 6. PyPI is a different registry. 33 projects with Talocode as the author, or a talocode- name. The recent API's last-month field sums to 371. Its last-week field sums to 192. talocode-loop, talocode-tokenlane, and talocode-vaultlane are 0 on the month field and 5, 19, and 15 on the week, so I am not treating 371 as complete. Neither registry says which download was a person and which was an agent. @talocode @tryteraai

I checked the official mint again this morning. Jupiter last updated that row on 21 October. Price about $0.01067. Market cap about $5,337. Liquidity about $185. 11 holders. My Tera wallet still holds 530. None of that has moved. The hold is the product. Official mint only, linked in Blockchain Lab, once a month. In October, 530 was the builder tier and the claim was 10,000 credits. The tokens stayed in the wallet. This is not equity, and I am not telling you the price will move. If you want the credits, buy only this mint, then open the wallet and link it. jup.ag/tokens/6ptxwABxQz8zMh… teraai.chat/wallet teraai.chat/lab/blockchain 6ptxwABxQz8zMhwhiPeVgRgWjGMdVcEBFBv8v8C3ory @talocode @tryteraai

Holding the official $TCODE mint is how the monthly @talocode Cloud credit claim works. The credits run the product APIs at dashboard.talocode.site. They are usage, not cash. The token is not equity. Do not send $TCODE to @talocode. One credit is $0.01. Link the wallet that holds the mint, then claim at dashboard.talocode.site/bill…. Per UTC month: 1 or more = 1,000 credits 100 or more = 10,000 credits 1,000 or more = 100,000 credits 5,000 or more = 500,000 credits A $5 top-up is a purchase. A hold is the monthly claim. They are not the same credits. Official mint only: 6ptxwABxQz8zMhwhiPeVgRgWjGMdVcEBFBv8v8C3ory @talocode @tryteraai

This breakdown of Nigeria’s wealth ladder is one of the clearest explanations I have seen of the gap between the poverty numbers and the real ownership of productive assets. The fact that roughly 140 million people sit below the national poverty line while a handful of people control industrial-scale wealth is not just a social issue — it is also an ownership issue. The part that stood out most is the observation that you can still own a piece of the top of that ladder for less than the cost of a litre of petrol. Nigerian stocks remain one of the clearest large-scale opportunities still available to ordinary people in the country. Many of the companies that sit at the higher levels of this ladder are listed, liquid, and still priced at valuations that do not fully reflect the size of the domestic market, the infrastructure build-out still required, or the long-term earnings power of the businesses. I started allocating a portion of my capital to Nigerian stocks for exactly that reason. The risk is real — currency, policy, liquidity, and governance all matter — but the asymmetry is also real. You do not need to reach Level 6 or Level 7 as an individual to own a small piece of the companies that operate at those levels. Consistent accumulation of quality listed businesses, held through cycles, is one of the few practical ways ordinary Nigerians can participate in the ownership side of the economy rather than only the wage side. At the same time, a growing number of people are also allocating to $TCODE. It sits in a different category — an early-stage token tied to the practical AI tools being built under @talocode — but the underlying logic is similar: own a piece of something that is being built rather than simply consume it. Different risk profile, different time horizon, same basic idea of moving from pure income to ownership. The ladder in the video is useful because it makes the distance visible. The next useful question is how many people at Levels 1–4 will deliberately start moving some capital into ownership vehicles (listed stocks, real assets, or selective early-stage projects) instead of treating every naira as purely consumption. That shift, done consistently, is what changes which level you are aiming for by 2030. @tryteraai

If you already use @tryteraai, this is the October loop. I ran it on my own wallet. Create a Tera Wallet. Hold the official $TCODE mint. Not a lookalike. Link that wallet in Blockchain Lab. The grant follows what you hold. Once per UTC month. The tokens stay in the wallet. Where I sit: 530. That is Builder. 10,000 credits for October, already claimed. The ladder on the page: 1+ is 1,000 credits a month. 100+ is 10,000. 1,000+ is 100,000. 5,000+ is 500,000. The free-plan cap is still 150. The grant is not the plan. teraai.chat/wallet teraai.chat/lab/blockchain/w… Official mint only: 6ptxwABxQz8zMhwhiPeVgRgWjGMdVcEBFBv8v8C3ory @talocode @tryteraai

I shipped this because @talocode cannot keep paying the cloud bill out of pocket while @tryteraai is the thing people actually use.

If you have been watching me for a while, you already know this did not start as a launch week. For months I have been building and improving @tryteraai in public. It is an AI product of @talocode. Same person. Same account. Same unfinished work, posted while it was still ugly. The first lesson was simple. Putting something live is not the same as helping someone learn. I could ship a chat box. Students could still cram, reread, and walk into an exam empty. The second lesson took longer. A long answer feels like progress. It is not. If they cannot start the next small step, and they cannot recall it tomorrow, the tool failed. I had to stop adding surface and make the loop tighter: shrink the topic, then test memory. The third lesson is the one I am still in. People will try Tera once. Getting them to come back the next week is the real product. I have been watching that the same way you have been watching me. Public building means you see the quiet weeks too, not only the shipping days. What I am working toward next is not a new brand. It is a student who opens Tera, finishes one topic, and comes back because it actually stuck. Exam pressure first. Same product, still usable anywhere. Phone browser. No theatre. I told that story on camera below

I brought @tryteraai Chat back online yesterday. Over the last few weeks, I have been building tools for agents: research, verification, policy controls, retries, tracing, and messaging workflows. But a pattern kept becoming clearer. The value is not an agent producing more output. The value is an agent helping work become more legible. What did it research? What did it change? What evidence supports the result? What still needs a human decision? This week, I gave an agent access to @talocode infrastructure. It researched better workflow patterns, saved primary-source findings into a reusable project artifact, and helped produce a full MessageLane developer tutorial. None of that should mean an agent gets to publish, send messages, or make consequential decisions without a clear boundary. That is the direction I want to keep building toward. Tools that help people and agents move faster, while making the important work easier to inspect, interrupt, verify, and improve. @tryteraai Chat is back because I want to learn what it becomes when it is used for real thinking, not just quick answers. Still early. Still improving. But back online.

New TeraAI video is live. Topic: studying when you don’t feel motivated. This one is for students who know they should study, but feel stuck before they even start. The idea is simple: don’t wait for motivation. make the task smaller. start with 5 minutes.

I just analyzed the X algorithm now. And most people still do not understand what changed. The feed is no longer just vibes, likes, and luck. It is becoming a full retrieval and ranking machine.

TeraAI update: I have been doing a lot of quiet infrastructure work behind the scenes. Not the flashy kind. The kind that makes the product stronger. Here is what changed. @Teraaiguide chat generation now runs through a proper API route instead of depending directly on Next.js server actions. That means fewer weird stale action errors. More stable responses. Cleaner client and server separation. I also moved the full AI generation flow into a shared engine so the same logic can power the web app, future mobile app, and other Tera clients without duplicating code. Credits also got a major improvement. Free credits now last much longer. Roughly 5,000 AI tokens now consume 1 credit. I also reset user limits so existing users get a fresh usage window. The goal is simple. Let more people actually learn with Tera before hitting limits. I also added important account emails. New users get a welcome email. Users get notified when credits run out. Paid users get subscription started, cancelled, and expired emails. Plus users can send team invite emails. All handled with proper logging and dedupe so users do not get spammed. Admin and usage reporting also got stronger. Better error visibility. Better health checks. Cleaner credit tracking. More reliable profile usage data. The mobile foundation is also moving forward with the Expo SDK 54 upgrade. A lot of this is invisible work. But invisible work is what turns a demo into a real product. Tera is becoming more stable, more generous, and more ready for real users. One commit at a time. teraai.chat

My product @Teraaiguide got 80 users and 0 paying users yet

It depends on how you use it. I built an AI Learning Companion @Teraaiguide to help me learn concepts deeply and used @grokipedia as the source of truth

Naa @Teraaiguide is better