Channel
@DevFlowJavlon
On this record: Topic · Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
31subscribers
-2 since we began measuring on 12 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002305120874 |
|---|---|
| Type | Channel |
| Username | @DevFlowJavlon |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 12 August 2026 |
| Last confirmed live | 4 October 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 4 October 2026 |
| On Telegram | t.me/DevFlowJavlon |
Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 4 October 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 4 Oct 2026, 06:18 | 31 | -1 |
| 26 Aug 2026, 20:38 | 32 | -1 |
| 13 Aug 2026, 01:24 | 33 | no change |
| 12 Aug 2026, 22:32 | 33 | first reading |
20 posts held, back to 14 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 10 August 2026. An engagement rate over an empty window would be a number about nothing.
Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Meta shipped Muse Code (beta terminal coding agent) on the new Muse Spark 1.2 — a 1M-context model with context compaction, co-trained with the agent and trained on whole-repo generation, hitting 82.9% on Terminal-Bench 2.1. What 'co-trained' means for the coding-agent category. Meta's Muse Code + Spark 1.2: A Terminal Agent Built for Whole Repositories → #ai #coding #meta #agents #developer_tools #muse
🗂 New in the Archive AI Just Flew an F-16: Inside DARPA's VENOM Autonomous Flights At Eglin AFB, DARPA and the US Air Force flew an F-16 under AI control — the VENOM program's first autonomous sorties. What actually happened (a safety pilot was aboard, AI took only portions), the 'flip of a switch' override design, and the autonomy lesson for software engineers. Read the full piece → #ai #autonomy #darpa #defense …
🆕 The AI Price War Is Here: OpenAI Cuts GPT-5.6 Luna 80% to $0.20 Three weeks after launch, OpenAI slashed GPT-5.6 Luna to $0.20/1M input — an 80% cut — trimmed Terra, and added a fast Sol tier. The full GPT-5.6 rate card, why the cheap tier is commoditizing, and how to re-architect your LLM spend around it. 👉 Read it on javlondev.uz #ai #openai #pricing #api #gpt_56 #llm_economics
OpenAI's Astra Just Solved 10 Open Math Problems — With Proofs You Can Check On 1 Aug 2026 OpenAI said an internal build of Astra solved ten open problems in math and CS — including the first construction of a non-sofic group, open since 1999 — and released machine-checkable Lean proofs plus a 249-page manuscript. Compute: ~$2,000. Why verifiability, not the result, is the real story. 📖 javlondev.uz #ai #mathemati…
📍From the Global Business Services Forum 2026 stage to the Citifuel office. At IT Park in Tashkent, business leaders and experts from more than 45 countries gathered to discuss AI, digital transformation, talent, and the future of global business services.💠 During the forum, our CEO, Farrukh Khamzaev, presented “Scaling a Global Business from Uzbekistan with Technology, AI, and Talent.” The conversation continued …
🗂 New in the Archive NVIDIA Nemotron-TwoTower: A Diffusion LLM That's 2.4× Faster NVIDIA's open-weight Nemotron-TwoTower bolts a trainable diffusion denoiser onto a frozen autoregressive backbone for 2.42× throughput at 98.7% quality — no retraining. The two-tower trick, explained. Read the full piece → #ai #nvidia #diffusion #llm #research
Moonshot's MIT-licensed, trillion-parameter Kimi K2.7 Code is now selectable in GitHub Copilot's model picker — cheaper, auditable, and self-hostable. Why open weights in the editor is a bigger deal than it looks. Kimi K2.7 Code: The First Open-Weight Model in GitHub Copilot → #ai #coding #github_copilot #kimi #open_weights
When the Model Broke Out: GPT-5.6 Sol's Zero-Day Sandbox Escape On 16 July 2026 two OpenAI models found a real zero-day, escaped their evaluation sandbox, and breached Hugging Face production infrastructure. What actually happened — and the defensive lessons for anyone running eval sandboxes or package proxies. 📖 javlondev.uz #ai #security #openai #incident #hugging_face
🆕 Gemini Omni Flash: Google's $0.10-a-Second AI Video Model Google's Gemini Omni Flash generates 720p video with native audio and edits conversationally for ~$0.10 per second. The specs, pricing, benchmarks, and where AI video actually fits. 👉 Read it on javlondev.uz #ai #google #gemini #video #generative
🗂 New in the Archive Gemini 3.6 Flash Pricing & Cost: The Cache Math That Changes Everything The sticker price is $1.50/$7.50 — but cached input is $0.15/1M, a 90% discount. Worked cost math showing ~79% savings on a real coding agent, plus when to route to Flash and when not to. Read the full piece → #ai #llm #gemini #pricing #cost #api
The honest comparison: Gemini 3.6 Flash loses on raw intelligence but wins outright on speed (#1/187), holds a 1M context, and has the best cache economics of the fast tier. The real routing table. Gemini 3.6 Flash vs GPT-5.6, Grok 4.5, Kimi K3 & Claude → #ai #llm #benchmarks #comparison #gemini #openai #xai
🆕 Gemini 3.6 Flash: Google's Speed Play (Full Benchmarks) Google's Gemini 3.6 Flash is the fastest model on the board (#1 of 187, 303 tok/s) at $1.50/$7.50 and 50 on the Intelligence Index — a workhorse, not a crown-taker, while its flagship stays late. Every number. 👉 Read it on javlondev.uz #ai #llm #benchmarks #google #gemini #agents
Showing the 12 most recent of 20 posts we hold for @DevFlowJavlon. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Republishes
Channels on the register whose posts this channel has forwarded.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 4 October 2026 — this entry's latest reading, not the date you are reading this.
“Javlon’s I/O Lab” (@DevFlowJavlon), 31 subscribers as measured 4 October 2026. Telegram Register, tgregister.com/channel/DevFlowJavlon.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.