We ran Britain's net zero future through 19,758 AI agents

Regional inequality and cost-of-living concerns appeared in every single simulated era. Not as the dominant topic — Carbon and Climate and Electric Vehicles held those positions throughout — but as a consistent secondary signal across all 25 years: 70 mentions in 2025–2030, 10 in 2030–2035, 50 in 2035–2040, 11 in 2040–2045, 9 in the final era. The numbers are small relative to the headline themes, but their persistence is the point. A simulation that shows regional inequality resolving as net zero milestones are achieved would tell one kind of story. A simulation that shows it refusing to disappear — even in the celebratory final rounds — tells a harder one.

Across all five eras, positive sentiment ran at 88–94%. The earliest period, 2025–2030, was the most optimistic at 95%, coinciding with the GB Energy Act and the first wave of clean power infrastructure. The most subdued era was 2040–2045 at 88%, when deep decarbonisation challenges — carbon capture at scale, hydrogen HGVs, residual emissions with no easy technical fix — came into focus.

The persistent positivity has a clear structural explanation: the institutional agents who drove most of the discourse were configured as predominantly supportive of net zero, reflecting real-world survey data on UK public and institutional opinion. This is a simulation of how discourse behaves given those stances, not a poll of public sentiment. What the slight downward drift from 95% to 88% between 2025 and 2045 does capture is something recognisable: the difference between policy optimism and implementation fatigue. The first five years are the easiest to be enthusiastic about. The last ten are where the hard residuals live.

The highest activity in the simulation, by some margin, came in the 2035–2040 era: 482 Twitter actions and 265 Reddit actions — nearly double the volume of the 2030–2035 clean power delivery period. The trigger was the petrol and diesel car ban, confirmed at round 120. Cost-of-living concerns also peaked in this era. Regional inequality, which ran as a persistent undercurrent across all five eras, sharpened as the transition costs became lived rather than projected.

This is worth pausing on. Of all thirteen milestone events — Clean Power 2030, 100GW offshore wind, net zero achieved — it was the car ban that generated the loudest simulated response. The reason is not surprising to anyone who has watched UK climate policy in the real world: the car ban is tangible. It sits in people's driveways. Every household with a petrol car has to reckon with it. It is not a carbon budget percentage or a grid capacity figure — it is a deadline that tells you what you will and will not be allowed to buy. Policy that lands in the driveway lands differently to policy that lands in the energy mix.

The architecture ran two tiers of AI agents in parallel on a Hetzner server over 100 hours of wall-clock time. Fifty-eight core institutional agents — government bodies, energy companies, NGOs, politicians, academics, media outlets — ran on Qwen-72B via Featherless.ai. The remaining 19,700 public personas, representing a cross-section of UK demographics by age, profession, region, income, and political leaning, ran on a local Qwen 2.5 3B model at zero API cost. The dual-model approach kept the simulation economically viable while enabling a population size no single-model run could match.

Each of the 300 rounds represented approximately one month of discourse. Thirteen milestone events were scheduled across the 25 years: the GB Energy Act and Heat Pump Mandate in 2025, Clean Power 2030 achieved, the petrol and diesel car ban in 2035, the tightest-ever Carbon Budget 6 in 2037, CCUS at scale in 2043, 100GW offshore wind in 2045, and Net Zero 2050 at round 295. Agents reacted to each milestone in character, within the constraints of their configured stance, influence weight, and activity level.

Across all five eras, positive sentiment ran at 88–94%. The earliest period, 2025–2030, was the most optimistic at 95%, coinciding with the GB Energy Act and the first wave of clean power infrastructure. The most subdued era was 2040–2045 at 88%, when deep decarbonisation challenges — carbon capture at scale, hydrogen HGVs, residual emissions with no easy technical fix — came into focus.

The persistent positivity has a clear structural explanation: the institutional agents who drove most of the discourse were configured as predominantly supportive of net zero, reflecting real-world survey data on UK public and institutional opinion. This is a simulation of how discourse behaves given those stances, not a poll of public sentiment. What the slight downward drift from 95% to 88% between 2025 and 2045 does capture is something recognisable: the difference between policy optimism and implementation fatigue. The first five years are the easiest to be enthusiastic about. The last ten are where the hard residuals live.

The highest activity in the simulation, by some margin, came in the 2035–2040 era: 482 Twitter actions and 265 Reddit actions — nearly double the volume of the 2030–2035 clean power delivery period. The trigger was the petrol and diesel car ban, confirmed at round 120. Cost-of-living concerns also peaked in this era. Regional inequality, which ran as a persistent undercurrent across all five eras, sharpened as the transition costs became lived rather than projected.

This is worth pausing on. Of all thirteen milestone events — Clean Power 2030, 100GW offshore wind, net zero achieved — it was the car ban that generated the loudest simulated response. The reason is not surprising to anyone who has watched UK climate policy in the real world: the car ban is tangible. It sits in people's driveways. Every household with a petrol car has to reckon with it. It is not a carbon budget percentage or a grid capacity figure — it is a deadline that tells you what you will and will not be allowed to buy. Policy that lands in the driveway lands differently to policy that lands in the energy mix.