First Principle Generative Algorithm (FPGA)
The First Principle Generative Algorithm (FPGA) is a proprietary metacognitive reasoning framework developed by the Council of Innovation Management (CIM) for systematic strategy design in technology-driven innovations.
FPGA enables innovators, researchers, and technology ventures to reason from first principles rather than relying on intuition, precedent-driven planning, or fragmented decision-making approaches.
Basics of FPGA reasoning algorithm
- Category of FPGA algorithm: Trans-disciplinary, Sector-agnostic Meta-Framework for Strategic-management
- Functional Ontology: Primary Truth: Living stakeholders,Physical objects Secondary Truth ( negotiable ) : social structures
- Epistemology: Implications-chaining from ontology, iterative hypothesis-testing against evidences
- First Principles Used: Consilience, Neuropsychology, Game-theory
- Constraints: Consilience, Contextual Social Structures
- Phases: exploration, convergence
- Methodology: Abductive and deductive reasoning, Human in The Loop
- Role of Data: Mainly for hypothesis testing
Profile of FPGA strategist
- Operates trans-disciplinary (not just multi-disciplinary, or inter-disciplinary)
- Can seamlessly generate public-policies to corporate strategies to personal guidance in any domain
- Requires minimal immersion period before performing as expert strategist in any-domain
- Provides crisp strategic recommendations with clear causal-chain
- Requires cognitive disposition towards First Principle Thinking, with ability to take cognitive load for transdisciplinary reasoning
- Requires minimum 3 years of rigorous training in the methodology before practising at professional levels
- Performance speed increases via logic compression, with increasing experience
What Makes FPGA Distinct
- First-principle driven: Fundamental decomposition of innovation decisions
- Metacognitive: Explicit mitigation of cognitive bias
- Domain-agnostic: Applicable across technology sectors
- Generative: Produces strategic pathways, and bespoke frameworks, not templates
- Unknown unknowns: discoverable and workable
- Information dependence: workable with approximate information
- Constraint aware: Specifically tests hypothesis against real world constraints
- Goal Definition: Revisable under epistemic impossibility to achive
- Decision-quality focused: Emphasis on reasoning rigor
- Capability: Generation of bespoke solutions and new domain-specific strategic-frameworks
Sample illustrations of FPGA derivations
- Entrepreneurship Supporting Policies need to focus on entrepreneurs as biological humans also along with their enterprises, because biological stakeholders are the primary truth.
- Entrepreneurship policy default, along with the statutory compliances should consider boot-strapped organic growth in default mode as 95% of enterprises never get venture-funding, while keeping provision for venture funding as special mode.
- Deep-tech startup may better scale-up as JV with established industries, than as VC funded scaling - because of the different cognitivive needs in R&D and in Industrail operations.
- Getting reliable escrow facility is vital for startups to overcome trust-deficit as new supplier, while avoiding uncertainty of payment recovery under credit sales.
- Porter's 5Forces framework is an emergent geme-theoric outcome of the engagement of the stakeholders' under the ontology of FPGA.
- As Biomarker detection is 'discovery', not 'invention'- the research funding for Biomarker detection and indexing must come from Government, while the privatisable 'invention' might be carried out by private-sector based on the open-source government-lead discoveries
Proprietary & Legal Notes
FPGA is a proprietary intellectual asset of the Council of Innovation Management.
Public descriptions are intentionally high-level and non-exhaustive.
FPGA is not a software product and is accessible only through authorised CIM-led initiatives. All rights are reserved.