系统层 01
prodia.dev // 正在运行

受控
自适应
软件

Prodia 是一个受控自适应软件平台。我们通过有量度的实验持续验证能力——每一次更改都是独立的、有证据的、可逆的。

无需信用卡即时部署
无需销售电话开发者优先流程
价值秒现自动发现
evolution-engine.sh 活动中
活动谱系
16 个节点
已接受
12
repo · 拓扑
运行中
正在分析lib/auth/session.ts确定
重构useAuth · O(n) → O(1)88%
正在验证快照完整性确定
认知

Prodia如何思考

一个想法,通过五个认知阶段追溯。每个阶段都会发出一个有类型证据——实时可见、计数并记录在决策账本中。

感知01假设02验证03治理04复合05
想法 · 追踪
运行中
阶段 01
感知

读取实时仓库、血缘和开放的机会界面。

发出 节省的创始人时间 · 发现重复的AuthAdapter ×11 — 避免了4小时的创始人时间
证据累积中
活动中
治理印章今天
1,284
已完成的转账本小时
41
链深度× 中位数
5.68
节省的创始人时间小时 · 24小时
312.4
已接受的演进今天
96
思想流
感知扫描 lib/auth/session.ts · 血缘 L-2041
假设候选:合并3个AuthAdapter克隆体
验证影子运行 · 14/14不变式成立
新手入职

连接您的代码库

粘贴代码库 URL。Prodia 将在三十秒内克隆、索引、感知、假设、验证并最终确定其首个决策。

$prodia 连接
尝试
空闲
流水线等待输入
克隆并索引
感知
假设
验证
确定
思维流 · 活动中空闲
等待代码库 · 在上方粘贴 URL 并点击连接
新手入职 · 档案
等待输入
运行模拟器以填充热点、候选突变和首个已确定的决策。

为软件开发的未来而生

企业 SaaS金融科技医疗保健安全DevOps

自主改进需要治理、可追溯性和信任。 Prodia 从设计之初就考虑到了这三点。

问题

软件停止改进
工程师停止工作的那一刻

传统开发

  • 改进手动进行
  • 技术债务累积
  • 工程能力有限

AI 编码工具

  • 按需生成代码
  • 无持续运行
  • 无长期学习

Prodia

  • 持续改进
  • 长周期运营
  • 从结果中学习
  • 随着时间安全地演进软件
运营原则

受控适应,持续验证

Prodia 评估代码库,识别候选改进,根据基线验证它们,并仅推广通过衡量的改进。

未声明。
未假设。
有证据的。
01

可衡量的软件演进

适应是被观察、衡量和记录的——而不是被声明的。

02

持续验证

每个候选更改在持久化之前都经过基线测试。

03

受控适应

更改在您的组织设定的策略边界内运行。

04

回滚保证

每个更改都可以被追踪、验证和即时恢复。

05

证据驱动的改进

结果为下一个决策提供信息——也为下一个主张的限制提供信息。

06

人工治理的工作流程

权限、审批范围和监督权仍在您的团队。

类别创建

超越AI编码

下一代软件开发不是更好的代码生成。它是持续自我改进的软件。

AI 编码工具
Prodia
编写代码
改进软件
需要提示
持续执行
基于会话
长周期运营
人工启动
自主改进
有限记忆
自适应记忆
工作原理

持续改进循环。

八个阶段,一个签名周期。每一次循环都会产生证据,淘汰错误的工作,并复合下一个决策。点击任何阶段以检查它消耗什么以及它产生什么。

活动中周期 #1284阶段 01 观察自动推进中
持续循环
观察
已发出 37 工件
已完成周期
0
本次会话
已探索阶段
1/8
点击查看
已发出的证据
95
已签名工件
价值复合增长
184.2k美元
等效年经常性收入
承诺层级好奇

在2分钟内生成您的第一个证据包。

Connect a public repo or pick a sample. We'll run a single shadow cycle and surface the highest-lift hypothesis.

运行免费演示Watch a recorded run insteadLow commitment · no signup · sample repo allowed
Visible Intelligence Layer

Five Agents. One Governed Pipeline.

Every Prodia decision moves through a transparent orchestration of specialised agents — observe the system thinking, in real time.

orchestrator · live
cycle 01041
PlanSpecBlueprintMutationEvidenceDecision01规划器Intent → Strategy02设计器Strategy → Blueprint03工程师Blueprint → Mutation04审阅者Mutation → Evidence05治理器Evidence → Action◂ governed feedback · every change reversible ▸
agent · 03active

工程师

Blueprint → Mutation

Responsibilities
  • Generate code mutations under blueprint constraints
  • Apply diffs in isolated sandboxes
  • Attach lineage & provenance metadata
Decisions
  • Diff strategy
  • Sandbox topology
  • Lineage anchor
Outputs
  • Signed diff bundle
  • Lineage node
  • Telemetry hooks
Live example
MUT-9421 · O(n) → O(1) session lookup · 14 files

hover a node · click to lock the dossier

Phase 04 · Agent Orchestration

A swarm, not a script.
Twelve specialists, one cohesion.

The pipeline you saw earlier runs once per cycle. Underneath, a constellation of role-specific agents works the codebase in parallel — leasing regions, exchanging signed evidence, and escalating to a human the instant policy demands it.

Agents online
12
active charters
Tasks in flight
12
parallel work units
Handoffs / min
18
inter-agent signals
Escalations
0
awaiting human co-sign
Cohesion
0.83
swarm alignment index
Live swarm · 12 specialists
tick · 1000
Task bus · signedtail -f
  • HANDOFFScout-01Refactor-02 · tangled call-graph in /billing/engine (depth 4)
  • EVIDENCEAccessor-12Refactor-02 · focus ring restored across 7 components
  • HANDOFFScribe-08Linguist-11 · 4 strings desynced from runtime intent
  • LEASEMigrator-10DepCurator-06 · reserving db/migrations · TTL 12m · reversible
  • ESCALATIONAuditor-05Human (sec) · scope drift in auth/session.ts — hold for co-sign
swarm cohesion · 82.5%sealed cycles this session · 17human co-signs pending · 0
Evolution Engine

Intelligence you can watch accrue.

Hypotheses are discovered from production telemetry, validated in shadow, proven in canary, and graduated to policy — or falsified and retired. Every promotion is signed, every retirement is recorded. Nothing is silent.

01
Discovery
2

Hypothesis mined from telemetry

02
Shadow
2

Runs offline against production traffic

03
Canary
1

Live on ≤5% of scope, probes watching

04
Adopted
1

Promoted into policy, falsifiable forever

05
Retired
1

Falsified or no lift, removed cleanly

Hypothesis
H-2041
Replace N+1 in invoice loader with batch query
Domain
billing
Lane
Canary
progress 42%
Signal
+1.8%conf 91%
Cumulative lift
+3.2% SCBI

Adopted hypotheses, compounding.

Adopted1
In flight5
Retired1
Falsification rate
50%of completed trials

High falsification is a feature. It means the bar is honest.

Adoption velocity · 24h

Every promotion signed · every retirement recorded · nothing silent

Phase 09 · Adaptive Memory

Memory That Compounds

Every sealed epoch leaves Prodia smarter than the last. Scrub the timeline to watch heuristics crystallise, cross-domain transfers fire, and the failure index decay as memory compounds.

Bus idle · seed memory horizon
E180E217E217
Heuristics
13
Transfers
9
FI
71.1
FI ↓
28.2%
Heuristics ledger
Durable rules sealed into platform memory
13
FI decay curve
Failure index vs E180 baseline
28.2% ↓
FI
71.1
ΔE
-0.74
Epoch
E217
Cross-domain transfers
Knowledge crossing domain boundaries
9
  • T-30analyticsinfraProbe-budget calibrationE215
  • T-27platformpaymentsQuorum-gated rolloutE211
  • T-24searchfrontendGraph-aware ranking signalE208
  • T-21paymentsbillingIdempotency re-promotionE205
  • T-18analyticsauthAnomaly-score gatingE201
  • T-15frontendinfraIdle-budget schedulingE198
Memory horizon · 38 sealed epochsPosition · E217 (38/38)Heuristics retained · 13/13
Long-Horizon Autonomy

Built For Long-Horizon Autonomy

Most AI systems fail when complexity accumulates. Prodia was designed to sustain intelligent behavior across extended execution windows while preserving goals, governance, and operational safety.

Cycles Executed
1,482,309
活动中
Mutations Attempted
28,491,204
活动中
Improvements Accepted
9,104,882
活动中
Rollbacks Triggered
184,201
活动中
Human Interventions
482
活动中
Why Enterprises Care

Potential business value, framed as evidence — not promises.

Prodia is designed to help organisations explore measurable improvements in maintenance, velocity, consistency, and governance — each supported by ongoing evidence generation.

01

Lower maintenance overhead

Explore reductions in repetitive engineering work through governed automation.

02

Faster improvement cycles

Shorten the path from opportunity to validated change inside policy boundaries.

03

Operational consistency

Apply the same validation and rollback discipline to every change, everywhere.

04

Governance visibility

Surface what changed, why, under whose authority, and how it can be reverted.

05

Safer experimentation

Run controlled adaptation behind baseline protection and change isolation.

06

Compounding evidence

Build a measurable record of outcomes that informs the next decision.

We avoid guarantees. Every claim above is framed as a hypothesis tested against measured outcomes in your environment.

ROI · Engineering Capacity

Reclaim engineer-quarters, not headcount.

Every assumption is exposed. Tune toil share, automation lift, and debt yield to your own telemetry — the model recalculates in real time.

Inputs · adjustable
Repo profile
48
$165
13w
Assumptions · exposed
38%
52%
0.31
Reclaimed capacity
4,685 hrs

360 hrs / week sustained over 13w horizon

$773K
loaded cost recaptured
Release-velocity uplift
1.26×

Projected lift in shipped increments / cadence, vs. unaided baseline.

+26%
vs. baseline
Debt burn-down
14.9 KLoC retired
of 142 KLoC
10.5%
week 0week 13
model.note — defaults calibrated against DORA, Stripe Developer Coefficient, and McKinsey DVI baselines. No hidden multipliers. Export the full assumption sheet during pilot scoping.
Governance Architecture

One system. Five guarantees.

Governance is not a feature list. It is a single mesh — a policy kernel and five interlocked guarantees, each enforced on every change, every agent, every artifact.

Risk Tiersscore 0 – 1
T1 · Trivial0.00 – 0.25
T2 · Low0.25 – 0.50
T3 · Elevated0.50 – 0.80
T4 · Critical0.80 – 1.00
POLICYKERNELRollbackIntegritySignatureProtectionValidationGatesRiskClassificationAuditability
Guarantee · 03
enforced

Validation Gates

No change reaches main without clearing the gate stack: type · contract · perf budget · semantic equivalence · isolated execution.

ENFORCES5-stage gate · isolated cluster · n=14
SAMPLE LOGcluster-01 · 14/14 pass · perf Δ +1.8%
live · last 24h
5
gates per change
live example streams · governed event ledger
streaming · frame 01/24
t0
t23
speed
Governance Mesh

Governance is a wired system, not a checklist.

Eight subsystems exchange signed signals continuously: policy verdicts, risk scores, lineage graphs, approval tokens, rollback proofs, rationales, ledger entries, and compliance attestations. Hover to trace any subsystem's dependencies; click to lock its dossier.

01Policy02Approval03Audit04Lineage05Risk06Rollback07Explainability08ComplianceGOVERNANCE MESH8 subsystems · 14 channelsALL SIGNALS SIGNED
Subsystem 03

Audit Ledger

Hash-chained record

发出
  • Signed entries
  • Replay bundles
Consumes
  • Every other subsystem
SLO owned
append < 80ms · 0 gaps
Live example
LEDGER#0x8af1 · 412k entries · chain intact
Governance Systems

Six wired systems. One governed surface.

Rollback Integrity, Transfer Learning, Core Safety, Signature Protection, Risk Classification, and Validation Gates run as one live mesh. Trace any system to its peers, then take the controls for yourself in a free guided demo.

LockedQ5 · Risk Classification
R1RollbackT2TransferS3SafetyK4SignatureQ5RiskV6GatesGOVERNED CORE6 systems · 12 channelsALL SIGNED · ALL REVERSIBLE
System Q5

Risk Classification

Continuous tiered scoring across every in-flight action. Tier crossings raise approver count; trip lines halt execution and arm rollback.

发出
  • Risk scores
  • Trip signals
  • Tier deltas
Consumes
  • Lineage scope
  • Probe telemetry
  • Historical falsifications
SLO owned
score refresh < 2s · calibration drift < 3%
Live example
RISK-5102 · tier=low · trip=false
Field proof
97.4% calibration accuracy (90-day window)
Take the controls

Walk the six systems in a free guided demo — no install, no card.

Step through Rollback, Transfer, Safety, Signature, Risk, and Gates on your own scenario. Prefer to read first? Open the trust dossier or book a 20-minute pilot briefing instead.

Trust Architecture

Five boundaries between intent and effect.

Every action travels a signed path: Human → Policies → Governance Layer → Agent Swarm → Actions. Each boundary is explainable, blockable, and auditable. Hover to inspect; click to lock a stage.

BOUNDARY 01BOUNDARY 02BOUNDARY 03BOUNDARY 04Human01Intent & AuthorityPolicies02Declarative Guardrails治理03Decision CourtAgent04Constrained ExecutionActions05Reversible Effects
Stage 03 · 3 of 5

Governance Layer

Decision Court

Live example
GOV-3318 · verdict=admit · 4 checks · ledger#0x8af1
Validates
  • Plan validity & rollback proof
  • Falsification tests passed
  • Lineage & provenance complete
Blocks
  • Plans without rollback
  • Unfalsifiable claims
  • Stale lineage
已发出的证据
  • Signed verdict
  • Hash-chained ledger entry
  • Replay bundle

No stage can be skipped · every boundary is hash-chained to the next

Evidence

Measured. Not Marketed.

Every claim Prodia publishes is reducible to a measurement, a method, and an entry in the decision ledger. Inspect the streams the system reports about itself.

live measurement
sealed 11s ago
frozen baseline
epoch − 12now
SCBI

+38.4% capability index

+4.1 vs. prior epoch
what we measure

Self-Calibrated Benchmark Index — measured drift against a frozen, blinded task corpus.

method

Index recomputed every cycle against a frozen, blinded task corpus. Reported as a delta against the prior epoch. Falsification gates remove unstable mutations before they enter the score.

$ ledger://epoch/2026.05.E217
Open in decision ledger
Compounding

The Lineage Map

Every accepted mutation chains to its parent across epochs, and ports across repos through transfer hops. Compounding is not a metaphor — it is a graph you can trace.

epoch explorer
E212 E2176 epochs
17 mutations4 hops
E212E213E214E215E216E217d1d1d1d2d2d2d3d3d2d4d3d5d5d3d6d6d4
lineage · graph
compounding
coreedgeledgerlineagetransfer
lineage · dossier
ledger://E217.B05
epoch E217 · core
Compounded refund net
depth
fi averted
11.4h
Δ reliability
+3.6%
lineage path
01AuthAdapter collapseE212
02Session lineage unifyE213
03BillingEngine refund pathE214
04Refund rollback rehearsalE215
05Billing chain extend d5E216
06Compounded refund netE217
transfers in range · E212–E217
4 hops
corpus · E212–E217
mutations
17
max depth
transfer hops
4
fi averted
82.7h
What We Believe

Autonomous software engineering is a testable hypothesis.

We believe software can become more adaptive, more maintainable, and more resilient through governed, evidence-based automation.

We do not claim that autonomous software engineering is solved.

Our focus is generating evidence, measuring outcomes, and continuously improving safety, reliability, and effectiveness.

Principle

Claims require evidence

Every capability statement is bounded by what we have actually demonstrated.

Principle

Outcomes are published

We publish outcomes, limitations, and lessons learned as part of responsible development.

Principle

Status is honest

Demonstrated, validating, researching, future — each label means something specific.

Founding Partner Program

Join The Founding Partner Program

Early Access

Limited

Be among the first teams to connect a repository and experience continuous autonomous improvement.

Request Access

Design Partners

By invitation

Shape the platform alongside our research team. Deep collaboration on capabilities and roadmap.

Request Access

Enterprise Pilots

Approval required

Production-scale evaluation with full governance, audit, and compliance support.

Request Access
Get Involved

What If Your Software
Improved While You Slept?

Join the organisations exploring autonomous software evolution.