The Toyota group extended the tender period for its bid to privatize a key unit, signaling the Japanese conglomerate needs more time to rally shareholder support. https://www.japantimes.co.jp/business/2026/02/12/companies/toyota-unit-tender-period-delay/?utm_medium=Social&utm_source=mastodon #business #companies #toyota #toyotaindustries #stocks #investments #elliottinvestmentmanagement

The Pentagon is pushing the top AI companies to make their artificial-intelligence tools available on classified networks without many of the standard restrictions that the companies apply to users. https://www.japantimes.co.jp/business/2026/02/12/tech/pentagon-ai-classified-networks/?utm_medium=Social&utm_source=mastodon #business #tech #pentagon #us #ai #openai #anthropic #google #xai

Tens of thousands of cars are being exported from China to Russia under gray-market schemes that often circumvent Western and Asian government sanctions and automakers' commitments to exit the Russian market, data shows. https://www.japantimes.co.jp/business/2026/02/12/economy/foreign-cars-russia-china-sanctions/?utm_medium=Social&utm_source=mastodon #business #economy #mercedesbenz #cars #carmakers #china #ukraine #russia #russiaukrainewar

Toyota said Wednesday that it will begin sales of its first locally produced electric vehicle in the United States. https://www.japantimes.co.jp/business/2026/02/12/companies/toyota-us-made-evs/?utm_medium=Social&utm_source=mastodon #business #companies #toyota #electricvehicles #cars #carmakers

Production of fish paste products has begun to rebound in Japan after decades of declines amid lower demand. https://www.japantimes.co.jp/business/2026/02/12/japan-fishpaste-products-rebound/?utm_medium=Social&utm_source=mastodon #business #food #fish #kibun

Shiseido’s fourth quarter earnings and full-year forecast beat analyst estimates, prompting the stock to surge as much as 15% in Tokyo trading on Thursday. https://www.japantimes.co.jp/business/2026/02/12/companies/shiseido-shares-up-on-earnings/?utm_medium=Social&utm_source=mastodon #business #companies #shiseido #cosmetics #chinajapanrelations

RE: https://mamot.fr/@pluralistic/116056780900371801

This is what I mean when I say that politicians are supposed to be lobbyists for the people: Not only should they not be so easily swayed by corporate marketing blitzes - it's literally their job to stand firm on the public's interests in face of such efforts.

Corporate lobbyists are - again, quite literally - their adversaries & we have to start yeeting every pol who doesnt't treat them as such.

#politics #lobbyism #tech #business @pluralistic

Prime Minister Sanae Takaichi’s landslide election win saw a largely positive initial response from investors. But they remain wary of another market meltdown over her expansive spending plans. https://www.japantimes.co.jp/business/2026/02/12/markets/bond-market-wary-takaichi-spending/?utm_medium=Social&utm_source=mastodon #business #markets #bonds #japaneseeconomy #sanaetakaichi #debt #boj #taxes #consumptiontax

Production of fish paste products has begun to rebound in Japan after decades of declines amid lower demand. https://www.japantimes.co.jp/business/2026/02/12/japan-fishpaste-products-rebound/?utm_medium=Social&utm_source=mastodon #business #food #fish #kibun

RE: https://mamot.fr/@pluralistic/116056780900371801

This is what I mean when I say that politicians are supposed to be lobbyists for the people: Not only should they not be so easily swayed by corporate marketing blitzes - it's literally their job to stand firm on the public's interests in face of such efforts.

Corporate lobbyists are - again, quite literally - their adversaries & we have to start yeeting every pol who doesnt't treat them as such.

#politics #lobbyism #tech #business @pluralistic

The top executive at Meta's Instagram defended the platform's choices around features that some company insiders called harmful to young users, at a trial on claims the app helped fuel a ​youth mental-health crisis. https://www.japantimes.co.jp/business/2026/02/12/tech/instagram-ceo-mental-health-trial/?utm_medium=Social&utm_source=mastodon #business #tech #instagram #meta #facebook #socialmedia #addiction #mentalhealth #adammosseri #markzuckerberg

French President Emmanuel Macron has returned to his “Made in Europe” push, putting him at odds with German Chancellor Friedrich Merz over how best to tackle Europe’s economic woes. https://www.japantimes.co.jp/business/2026/02/12/economy/macron-merz-buy-european/?utm_medium=Social&utm_source=mastodon #business #economy #france #eu #europe #emmanuelmacron #germany #friedrichmerz #economicindicators

Elon Musk has overhauled the management of his startup xAI ahead of a planned initial public offering that could rank among the largest ever, after merging the company with his rocket firm SpaceX. https://www.japantimes.co.jp/business/2026/02/12/tech/musk-xai-spacex-merger-ipo/?utm_medium=Social&utm_source=mastodon #business #tech #elonmusk #ai #tech #xai #spacex

Given Jim Ratcliffe has been complaining about the number of people who are on benefits in the UK, perhaps he should recall that nearly half of those recipients are in receipt of in-work benefits & as such the real beneficiaries are hie fellow businessmen who are seeing their profits supported by the state that is subsiding employment (thereby allowing firms to pay their workers less).

#inequality #business #benefits #politics

South Korea promised to help "Make American Shipbuilding Great Again,” pitching its shipyards as a model to revive U.S. manufacturing, but in reality, the sector relies on low-paid migrants and is plagued by accidents. https://www.japantimes.co.jp/business/2026/02/12/koreans-shipbuilding-trump/?utm_medium=Social&utm_source=mastodon #business #shipping #us #manufacturing #southkorea #donaldtrump #hyundai #immigration #shipbuilding

Given Jim Ratcliffe has been complaining about the number of people who are on benefits in the UK, perhaps he should recall that nearly half of those recipients are in receipt of in-work benefits & as such the real beneficiaries are hie fellow businessmen who are seeing their profits supported by the state that is subsiding employment (thereby allowing firms to pay their workers less).

#inequality #business #benefits #politics

Akio Toyoda, chairman of Toyota, has been named a 2026 inductee to the U.S. Automotive Hall of Fame. He will be the fourth member of the company's founding Toyoda family to receive the honor. https://www.japantimes.co.jp/business/2026/02/11/companies/toyota-chairman-automotive-hall-of-fame/?utm_medium=Social&utm_source=mastodon #business #companies #akiotoyoda #toyota #carmakers #usautomotivehalloffame #cars

Government Software at the Crossroads

The software industry is undergoing its most significant transformation since the rise of cloud computing. Last week, $285 billion in market cap evaporated from software stocks in a single day — a selloff traders are referring to as the “SaaSpocalypse.” Investors seem to have reached the conclusion that AI agents are going to reshape how organizations buy and use software. I don’t think they are wrong.

Private sector companies are scrambling to adapt. But there’s another sector that may be even more exposed to this shift, and far less prepared for it: government.

Really Bad Timing

Many government technology leaders are being asked to make major procurement decisions during a period of unprecedented instability in the software industry. The assumptions that have traditionally guided smart technology investments for the past decade — buy commercial off-the-shelf software, pay per seat, move to the cloud — may no longer hold.

The problem is that the government procurement cycle is slow by design. Decisions being made today will bind agencies to contracts lasting as long as five to seven years. An enterprise agreement signed this in Q1 could lock an agency into paying for software seats that AI tools have made redundant by year three — with no easy off ramp.

The traditional mismatch between government procurement cycles and the pace of change in the technology industry is becoming even more acute in the AI era. This problem is only going to get worse.

Still Fighting the Last War

Most government technology leaders are still operating from a playbook written in the 2010s. The common strategy is to modernize legacy systems by migrating to commercial SaaS products. This may have been the right move ten years ago. Cloud-based software offered better security, lower maintenance burden, and faster feature updates than aging on-premise systems.

But the landscape has shifted significantly, particularly in the last 12 months. The value of software is migrating from user interfaces to APIs, from per-seat licenses to outcomes, from products to orchestration layers. AI agents don’t need polished dashboards — they need access to data and the ability to execute tasks. A procurement strategy optimized for buying seats for commercial interfaces may be optimizing for exactly the wrong thing.

The mental model of “replace the old thing with the new commercial thing” simply doesn’t account for a world where AI agents can wrap existing systems, orchestrate actions across them, and generate deliverables without requiring wholesale replacement of underlying infrastructure.

A Matter of Trust

Another concern for government organizations is that the organizations best positioned to advise them on these shifts – existing legacy vendors – are often not incentivized to do so.

Large systems integrators and consultancies that guide government technology strategy make their money from complexity and labor hours. A message of “you may need fewer tools, less customization, and smaller teams — orchestrated by AI” does not align with their business model. So government leaders may not hear that message they need to hear until the shift is already obvious and the contracts are already signed.

Even absent malice, the fact that these changes are misaligned with existing legacy vendors business models means that simply won’t be incentivized to provide the information government leaders need to hear, when they need it.

The Build-vs-Buy Calculus Is Changing Fast

There’s another assumption baked into traditional government technology strategy that deserves a reexamination – the economics of building software.

For a long time, this logic was straightforward. Custom software development was expensive, slow, and risky. Projects routinely ran over budget and past deadlines. Maintaining bespoke systems required specialized staff that agencies struggled to hire and retain. Commercial off-the-shelf products offered a potential way out — vendors amortize development costs across many customers, governments benefit from continuous improvement and transfer the maintenance burden to external organizations built better for it.

This logic has driven the preference for COTS and SaaS procurement. Why build it when you can buy it?

But the economics of software development have shifted dramatically in the past eight months. AI coding assistants have moved from novelty to core infrastructure. Recent analysis suggests that a meaningful percentage of code commits on major platforms are now authored by AI — not assisted by AI, but generated by it. The changes we are seeing are not trivial. Entire codebases are being refactored by AI agents working in parallel. This will change the math on custom development. The cost of building software tailored to an agency’s specific needs — rather than adapting workflows to fit a vendor’s product — is dropping rapidly.

None of this means commercial software will go away overnight. But it does mean the factors that made COTS and SaaS the default safe choice are eroding. The question “should we buy or build?” deserves renewed analysis based on current economics, not assumptions inherited from an era when custom development was synonymous with cost overruns and contractor dependency.

A Different Kind of Risk

The traditional risk calculus in government technology focuses on project failure — the big modernization effort that goes over budget, misses deadlines, or fails to deliver promised functionality. These are real risks, and they’ve shaped a culture of caution around major technology investments in government.

But there’s a different kind of risk emerging: the risk of committing to a technology strategy that becomes obsolete mid-execution. The risk isn’t that the project fails — it’s that it succeeds at the wrong thing. An agency could execute flawlessly on a cloud migration strategy and still end up paying for years of software licenses that deliver diminishing value as AI reshapes workflows around them.

This is new territory. The frameworks government uses to evaluate technology risk weren’t designed for a world where the underlying economics of software could shift dramatically within a single contract period.

What Would A Safe Approach Look Like?

Given all this uncertainty, what would a prudent approach to government software strategy look like in early 2026? I think it looks something like this:

Shorter commitments where possible. The long-term enterprise agreement that locked in favorable pricing made sense in a stable environment. In a period of rapid change, flexibility may be worth more than discounted pricing. Agencies should scrutinize contract terms that limit their ability to adapt quickly.

Invest in understanding before deciding. Before committing to a modernization path, invest in truly understanding existing systems — not just their code, but the institutional knowledge and business logic they embody. That understanding has value regardless of whether you eventually replace, wrap, or extend those systems. Methodologies like SpecOps that focus on generating verified specifications of legacy system behavior offer a way to preserve optionality while the landscape clarifies.

Watch the API layer, not the interface. When evaluating software, pay attention to how well it exposes functionality via APIs, not just how polished its user interface is. The interface matters less in a world where AI agents are increasingly the “users” of enterprise software.

Cultivate independent perspective. Seek out advisors whose business model doesn’t depend on selling implementation services, and who have expertise in using AI to develop solution. The analysis that matters most right now is the analysis that might recommend doing less, not more.

The Time Is Now

Government technology decisions have always involved balancing risk against opportunity. What’s different now is the speed of change in the underlying assumptions.

The organizations that navigate this transition the best will be those that recognize the moment for what it is: not a time to double down on the strategies of the past decade, but a time to preserve optionality, invest in understanding, and resist the pressure to lock in long-term commitments based on a model of software value that may already be shifting beneath our feet.

The window to make these adjustments is right now — before the next round of multi-year contracts for COTS or SaaS software are signed, and before government agencies find themselves paying for a model of software that the rest of the world has moved on from.

Government Software at the Crossroads

The software industry is undergoing its most significant transformation since the rise of cloud computing. Last week, $285 billion in market cap evaporated from software stocks in a single day — a selloff traders are referring to as the “SaaSpocalypse.” Investors seem to have reached the conclusion that AI agents are going to reshape how organizations buy and use software. I don’t think they are wrong.

Private sector companies are scrambling to adapt. But there’s another sector that may be even more exposed to this shift, and far less prepared for it: government.

Really Bad Timing

Many government technology leaders are being asked to make major procurement decisions during a period of unprecedented instability in the software industry. The assumptions that have traditionally guided smart technology investments for the past decade — buy commercial off-the-shelf software, pay per seat, move to the cloud — may no longer hold.

The problem is that the government procurement cycle is slow by design. Decisions being made today will bind agencies to contracts lasting as long as five to seven years. An enterprise agreement signed this in Q1 could lock an agency into paying for software seats that AI tools have made redundant by year three — with no easy off ramp.

The traditional mismatch between government procurement cycles and the pace of change in the technology industry is becoming even more acute in the AI era. This problem is only going to get worse.

Still Fighting the Last War

Most government technology leaders are still operating from a playbook written in the 2010s. The common strategy is to modernize legacy systems by migrating to commercial SaaS products. This may have been the right move ten years ago. Cloud-based software offered better security, lower maintenance burden, and faster feature updates than aging on-premise systems.

But the landscape has shifted significantly, particularly in the last 12 months. The value of software is migrating from user interfaces to APIs, from per-seat licenses to outcomes, from products to orchestration layers. AI agents don’t need polished dashboards — they need access to data and the ability to execute tasks. A procurement strategy optimized for buying seats for commercial interfaces may be optimizing for exactly the wrong thing.

The mental model of “replace the old thing with the new commercial thing” simply doesn’t account for a world where AI agents can wrap existing systems, orchestrate actions across them, and generate deliverables without requiring wholesale replacement of underlying infrastructure.

A Matter of Trust

Another concern for government organizations is that the organizations best positioned to advise them on these shifts – existing legacy vendors – are often not incentivized to do so.

Large systems integrators and consultancies that guide government technology strategy make their money from complexity and labor hours. A message of “you may need fewer tools, less customization, and smaller teams — orchestrated by AI” does not align with their business model. So government leaders may not hear that message they need to hear until the shift is already obvious and the contracts are already signed.

Even absent malice, the fact that these changes are misaligned with existing legacy vendors business models means that simply won’t be incentivized to provide the information government leaders need to hear, when they need it.

The Build-vs-Buy Calculus Is Changing Fast

There’s another assumption baked into traditional government technology strategy that deserves a reexamination – the economics of building software.

For a long time, this logic was straightforward. Custom software development was expensive, slow, and risky. Projects routinely ran over budget and past deadlines. Maintaining bespoke systems required specialized staff that agencies struggled to hire and retain. Commercial off-the-shelf products offered a potential way out — vendors amortize development costs across many customers, governments benefit from continuous improvement and transfer the maintenance burden to external organizations built better for it.

This logic has driven the preference for COTS and SaaS procurement. Why build it when you can buy it?

But the economics of software development have shifted dramatically in the past eight months. AI coding assistants have moved from novelty to core infrastructure. Recent analysis suggests that a meaningful percentage of code commits on major platforms are now authored by AI — not assisted by AI, but generated by it. The changes we are seeing are not trivial. Entire codebases are being refactored by AI agents working in parallel. This will change the math on custom development. The cost of building software tailored to an agency’s specific needs — rather than adapting workflows to fit a vendor’s product — is dropping rapidly.

None of this means commercial software will go away overnight. But it does mean the factors that made COTS and SaaS the default safe choice are eroding. The question “should we buy or build?” deserves renewed analysis based on current economics, not assumptions inherited from an era when custom development was synonymous with cost overruns and contractor dependency.

A Different Kind of Risk

The traditional risk calculus in government technology focuses on project failure — the big modernization effort that goes over budget, misses deadlines, or fails to deliver promised functionality. These are real risks, and they’ve shaped a culture of caution around major technology investments in government.

But there’s a different kind of risk emerging: the risk of committing to a technology strategy that becomes obsolete mid-execution. The risk isn’t that the project fails — it’s that it succeeds at the wrong thing. An agency could execute flawlessly on a cloud migration strategy and still end up paying for years of software licenses that deliver diminishing value as AI reshapes workflows around them.

This is new territory. The frameworks government uses to evaluate technology risk weren’t designed for a world where the underlying economics of software could shift dramatically within a single contract period.

What Would A Safe Approach Look Like?

Given all this uncertainty, what would a prudent approach to government software strategy look like in early 2026? I think it looks something like this:

Shorter commitments where possible. The long-term enterprise agreement that locked in favorable pricing made sense in a stable environment. In a period of rapid change, flexibility may be worth more than discounted pricing. Agencies should scrutinize contract terms that limit their ability to adapt quickly.

Invest in understanding before deciding. Before committing to a modernization path, invest in truly understanding existing systems — not just their code, but the institutional knowledge and business logic they embody. That understanding has value regardless of whether you eventually replace, wrap, or extend those systems. Methodologies like SpecOps that focus on generating verified specifications of legacy system behavior offer a way to preserve optionality while the landscape clarifies.

Watch the API layer, not the interface. When evaluating software, pay attention to how well it exposes functionality via APIs, not just how polished its user interface is. The interface matters less in a world where AI agents are increasingly the “users” of enterprise software.

Cultivate independent perspective. Seek out advisors whose business model doesn’t depend on selling implementation services, and who have expertise in using AI to develop solution. The analysis that matters most right now is the analysis that might recommend doing less, not more.

The Time Is Now

Government technology decisions have always involved balancing risk against opportunity. What’s different now is the speed of change in the underlying assumptions.

The organizations that navigate this transition the best will be those that recognize the moment for what it is: not a time to double down on the strategies of the past decade, but a time to preserve optionality, invest in understanding, and resist the pressure to lock in long-term commitments based on a model of software value that may already be shifting beneath our feet.

The window to make these adjustments is right now — before the next round of multi-year contracts for COTS or SaaS software are signed, and before government agencies find themselves paying for a model of software that the rest of the world has moved on from.