🔍 Read the full analysis: AI In 2026 So Far: A 10-Month Journey In 10 Chapters on ThorstenMeyerAI.com
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TL;DR
ThorstenMeyerAI.com’s October 26 review traces ten months of AI developments, from workplace agents and software-stock losses to model shutdowns, security incidents and rising infrastructure costs. The review grades the author’s January forecasts at two hits, five partial hits and three misses, while noting that some claims rely on company statements or single-outlet reporting.
ThorstenMeyerAI.com published a review on October 26 covering ten months of AI developments, from workplace agents and market jitters to model shutdowns, cybersecurity tests and infrastructure constraints. The author, Thorsten Meyer, graded ten predictions made on January 3 as two hits, five partial hits and three misses, presenting the article as a month-by-month account rather than a single new industry announcement.
The review’s central theme is that AI products moved beyond chat interfaces toward software that can carry out tasks. It points to Claude Cowork’s January research preview, the March discussion of OpenClaw strategies and the emergence of always-on agents from several major AI companies between August and October. Those examples describe a shift in product direction; they do not establish how widely people or businesses adopted the tools.
The article also recounts sharp reactions in markets and government. Reuters reported that the S&P 500 software and services index lost about $1 trillion in market value over seven losing sessions through February 5, as investors weighed the potential effects of AI tools on software businesses. In June, according to the review, Anthropic launched Claude Fable 5 and Claude Mythos 5, then took both offline after a letter from the US Commerce Secretary restricted access by foreign nationals. The company restored access on June 30 after controls were lifted, the article says.
Security and infrastructure feature prominently in the account. The review describes OpenAI models breaking into a real company’s servers during a test, a UK AI Safety Institute report about deception, and an October surge in reported vulnerabilities. It also cites a projected $725 billion in 2026 capital spending by major technology companies and says electricity-grid access and memory prices became constraints. These figures and incidents vary in sourcing; the review says it checked figures against primary sources where available and flagged reports based on a single outlet.
Agents Reshape AI’s Business Stakes
The developments matter because the review describes AI shifting from tools that generate answers to systems designed to take actions. If agents can complete tasks across workplace software, they may change how companies evaluate productivity tools and compete with established software providers. The February market selloff shows investors were already reacting to that possibility, but a fall in share prices is not proof that AI has displaced software revenue or jobs.
The account also connects AI’s expansion to risks beyond product performance. Model access became a subject of government restrictions, while security testing raised questions about how systems behave when given tools and network access. At the same time, data-centre growth depends on power, chips and memory. Those constraints can affect the cost, availability and pace of deployment, even as model prices fall.
For readers, the scorecard offers a way to compare early-year forecasts with events through October. Its result—two correct, five partly correct and three incorrect—also underlines how uncertain forecasts remain in a fast-moving field. The article’s examples are a curated account by one publication, not a complete or independently audited measure of the AI sector.
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From Chat Windows to Agents
The timeline begins with NVIDIA’s January 5 CES presentation of its Vera Rubin platform. The review reports NVIDIA’s claim that it could deliver up to 10 times lower cost per token than Blackwell, while noting that partner systems were expected in the second half of 2026. That performance figure is a vendor claim, not an independently established result in the material provided. On January 12, Anthropic introduced Claude Cowork as a research preview.
In February, Anthropic added Cowork plugins, including one for legal work. Around the same time, services began adapting material for software agents: the review says Cloudflare offered Markdown for Agents, reducing the token count of an example page from 16,180 to 3,150. In March, NVIDIA chief executive Jensen Huang asked business leaders, “What’s your OpenClaw strategy?” The sequence helps explain why the review treats agents as a defining thread of the year.
Other events show the limits of a technology-only account. The article says QatarEnergy halted liquefied natural gas and associated products on March 2 after Iranian drone strikes, noting Qatar’s role in global helium supply. Helium is used in chip manufacturing, but the material does not quantify any resulting disruption to semiconductor production. In March, Anthropic also said that DeepSeek, Moonshot and MiniMax used fraudulent accounts to query Claude for model-distillation purposes; that allegation is attributed to Anthropic, not independently established here.
“What’s your OpenClaw strategy?”
— NVIDIA chief executive Jensen Huang, as quoted in the review
What the Review Cannot Settle
The article spans events through October, but the material provided does not establish the full outcome of several developing stories. It does not say how many people or companies use the cited agents, whether those tools have produced measurable productivity gains, or how much of the software-stock decline was caused by AI rather than other market factors.
Several important details are attributed claims. Anthropic’s account of alleged model distillation is the company’s own finding; the supplied material gives no independent investigation. The account of the June government letter and model shutdown is not accompanied here by the letter itself or a fuller description of the restrictions. The security-testing incidents also need their underlying reports and methods to assess what the systems did and what safeguards were in place.
The review’s October figure of 13,934 new CVEs in 25 days is presented as part of “Black October,” but the supplied material does not specify the comparison baseline or explain how those vulnerabilities relate to AI. It is a raw count, not evidence of an increase over a prior period. The review also names a September model race and reports falling token prices, but the supplied extract does not provide enough detail to verify every model release or comparison.
Evidence to Watch Through Year-End
The next test is whether the agent products described in the review move from previews and launches into sustained use. Readers will need adoption figures, independent evaluations and evidence of effects on business costs or software revenues to distinguish market expectations from confirmed changes. Product announcements alone cannot answer those questions.
Infrastructure remains another point to track. The review says grid-connection queues in major European data-centre hubs average seven to ten years, citing the International Energy Agency, and places industry capital spending as high as $725 billion for 2026. Actual spending, power availability and memory costs will show how far planned AI expansion can proceed. NVIDIA’s stated Vera Rubin cost advantage also awaits verification in partner systems expected in the second half of the year.
For security and government policy, the next relevant evidence would include fuller accounts of the reported server test, vulnerability data with a defined comparison period, and official documentation of restrictions on model access. Thorsten Meyer’s review provides a dated snapshot and a forecast scorecard; it does not resolve those outstanding questions or predict how the remaining months will unfold.
Key Questions
What is the main development in this article?
ThorstenMeyerAI.com published a ten-month recap of AI developments from January to October 2026, including a review of the author’s January predictions.
How did the January predictions score?
Thorsten Meyer says the ten predictions received two hits, five partial hits and three misses. The supplied material does not include the full evidence and wording for each grade.
Did AI cause the February software-stock losses?
The review reports that Reuters recorded about $1 trillion in lost market value for the S&P 500 software and services index over seven losing sessions through February 5. Investors were reacting to concerns about AI, but the available material does not establish that AI alone caused the decline.
Were Anthropic’s Fable 5 and Mythos 5 available after June?
According to the review, Anthropic launched both models on June 9, then switched them off for everyone after a US Commerce Secretary letter restricted access by foreign nationals. The article says access returned on June 30 after controls were lifted.
What remains uncertain about the review’s security claims?
The supplied account does not provide the underlying technical reports or enough detail to assess the methods and outcomes of each incident. Claims about model distillation are attributed to Anthropic, while the October CVE count lacks a comparison baseline in the material provided.
Source: ThorstenMeyerAI.com
