Technical creator. Involved in everything AI, data, and tech

The edge computing market hit $168B in 2025. IoT devices are headed to 39 billion by 2030. And yet: most vector database are mot built for air-gapped or latency-critical environments. Healthcare. Manufacturing. Military. The cloud can't serve them, and nobody's building for them.
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An AI agent can find the right URL and still give you the wrong answer. I ran through a tutorial on building a web-aware agent with the OpenAI Agents SDK, and the product-price example shows why. Search finds the product page, but the current price may be rendered client-side.
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So the agent knows where the product is, but not what it currently costs. The pattern I liked was giving it two tools: Search → discover the page Fetch → retrieve the current page content How are your agents handling this gap? zenrows.com/blog/web-aware-a…
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“Managed Postgres” can mean very different things. At minimum, I’d expect patching, scaling, failover + backups to leave the team’s plate. Databricks’ Lakebase adds serverless scaling, PITR, branching, PgBouncer + pgvector. databricks.com/blog/managed-…
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Free is a great price. Well, 57.7s per task (AA's number, not mine) is also a great time to go make coffee :)
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I spent 47 days as one of several thousand African migrants seeking to enter Europe through the Sahara Desert and the Mediterranean Sea. Story on @fijnigeria tomorrow, Thursday and on Friday.
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Hii everyone, a closed mouth is a closed destiny so I’m here again to attempt to sell myself. My name is Ene, and I have extensive and highly profitable skills and experience in administration, writing, and community management. I unfortunately cannot apply to regular jobs because I didn’t finish school, but if you know any organizations that value work ethics and professional skills over degrees, please send the opportunities my way. I lost my previous job cause the employers didn’t want to put up with the new tax laws so they pulled out of Nigeria entirely. Also if you own a business in Abuja and you’re looking for an onsite manager or secretary, please look here. I promise I’m a very great staff. Please help me. Please🥹
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Google Custom Search JSON API is gone on Jan 1, 2027. If it is in your stack, do not just swap endpoints. Check your parser, pagination, domain restrictions, query params, quotas, and failure handling too. This migration guide by Octen breaks it down well octen.ai/versus/google-custo…
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A useful question before scraping data for fine-tuning: Would I be comfortable teaching the model from this source? This guide recommends official docs and expert-reviewed sources, while filtering out content farms and sources you cannot vouch for. zenrows.com/blog/web-data-ll…
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My 23year old sister is battling cancer. Donation link is in my bio
Never be ashamed to ask for help.
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If this pops up on your TL, please give us a repost, a quote and please tag anyone who can be of help. We still have a very long way to go.
This is Jazeel a 6 year old with three holes in his heart. His mother sent his picture to me, see blood in his eyes, I cried when I saw the picture, because I've witnessed a scenario where this boy had a seizure 😭 I cried that day. Read my chat with his mum this morning they need 8M for surgery. This is one of those times I really wished God blesses me the way I want 😭 @Wizarab10 @osemagnum @Dr
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Hi guys!! If you’re looking for an editor I’m your girl okay? :)
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Amazing stuff. Need to use Octen for my next portfolio project!
10 months ago, we started Octen with one belief: search infrastructure built for humans won't be enough for AI. Most of the industry saw the same shift, but kept building with a human-search mindset. AI doesn't search like humans. It fires hundreds of queries in parallel, reads everything it retrieves, and needs clean, grounded content back in milliseconds, at a cost that still works at scale. So we didn't adapt human search for AI. We rebuilt it from first principles. Today, Artificial Analysis published its independent Search API benchmark. Octen is the only major provider ranked Top 3 in all three dimensions that matter: #1 in speed #2 in cost efficiency Top 3 in search quality We're also the only provider in Artificial Analysis' "Most Attractive Quadrant" for search quality vs. cost. What makes me proudest is how we got here. Many companies on this leaderboard have been building for 3–5 years and have raised hundreds of millions of dollars. Octen is 10 months old and has raised just $10M. To me, product built per dollar raised is one of the most honest measures of technical strength in this industry. We've kept the team small but exceptional, moved fast, and put nearly everything into the core technology. People used to assume search had to trade off speed, cost and quality. We've shown it can be faster, cheaper and better at the same time. The product engine is working. Next, we're bringing Octen to every model, agent and physical AI product that needs to search. Humans search with Google. AI searches with Octen. We're just getting started. 🚀
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10 months ago, we started Octen with one belief: search infrastructure built for humans won't be enough for AI. Most of the industry saw the same shift, but kept building with a human-search mindset. AI doesn't search like humans. It fires hundreds of queries in parallel, reads everything it retrieves, and needs clean, grounded content back in milliseconds, at a cost that still works at scale. So we didn't adapt human search for AI. We rebuilt it from first principles. Today, Artificial Analysis published its independent Search API benchmark. Octen is the only major provider ranked Top 3 in all three dimensions that matter: #1 in speed #2 in cost efficiency Top 3 in search quality We're also the only provider in Artificial Analysis' "Most Attractive Quadrant" for search quality vs. cost. What makes me proudest is how we got here. Many companies on this leaderboard have been building for 3–5 years and have raised hundreds of millions of dollars. Octen is 10 months old and has raised just $10M. To me, product built per dollar raised is one of the most honest measures of technical strength in this industry. We've kept the team small but exceptional, moved fast, and put nearly everything into the core technology. People used to assume search had to trade off speed, cost and quality. We've shown it can be faster, cheaper and better at the same time. The product engine is working. Next, we're bringing Octen to every model, agent and physical AI product that needs to search. Humans search with Google. AI searches with Octen. We're just getting started. 🚀
Octen Search debuts third on the Artificial Analysis Search Index with a score of 77, achieving the fastest Time per Task at 16.9 seconds and one of the lowest Costs per Task We benchmarked Octen Search from @OctenAI using our search agent methodology: a fixed base model running inside our open-source agent harness, Stirrup, with tools for searching and fetching pages from the web. Only the provider behind the search tool changes. Key results of Octen Search with highlights enabled: ➤ Strong Search Index performance, led by BrowseComp: Octen Search scores 77 on the Artificial Analysis Search Index, placing third behind Perplexity Search (medium, 80) and Perplexity Search (high, 79), and level with Perplexity Search (low, 77). Octen performs particularly well on BrowseComp, scoring 86, just one point behind the leader. It also scores within one point of the leaders on DeepSearchQA at 80, while its AA-Omniscience score of 66 trails Firecrawl Search (73) and Perplexity Search (medium, 72) ➤ Fastest search across providers: Octen Search averages 0.2 seconds per query, 5x faster than the Perplexity Search variants at 1.0 to 1.2 seconds. Its Time per Task is 16.9 seconds, the lowest of any provider result, against a board range of 16.9 to 62.9 seconds ➤ Low Cost per Task: Octen Search costs $0.058 per Search Index task at a price of $1 per 1k search queries. Only TinyFish Search, which offers search for free, has a lower Cost per Task. For comparison, Perplexity Search (medium) costs $0.091 per task
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Sasi code is so brilliant with the chat vibe😭😭
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Everyone building AI agents knows the frustration of the search-then-fetch loop, as most search APIs stop at snippets. Then to actually read the pages, your agent has to call a second endpoint, and you end up paying an extra bill for that. We have a different attitude on what AI actually needs. That’s why we built the workflow differently at Octen. The whole pipeline is just one API call, and you get the URLs plus the full content, all in less than 62ms. Drop the separate fetch tools, try it now and get $5 free: octen.ai/platform/web-search
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I keep coming back to this question with RAG: Where should your data live? For some workloads, sending documents to a managed cloud stack is perfectly reasonable. For sensitive, regulated, or air-gapped environments, running embeddings, vector search, ....
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What was the mid break dance for😂😭😭
God😭😭😭😭
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I keep thinking about how much unnecessary context we throw at LLMs. Give an agent a 50-page website because somewhere in there is one sentence we need. Now the model has to sift through navigation, sidebars, footers, unrelated sections just to find one useful detail.
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Are you looking for a job? There are 17 new roles on Hackmamba DevTools job board Jobs for technical writing, content, GTM, and developer marketing Get that bag my friends 👀 -> bki.sh/lLPhzpq
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